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Journal articles on the topic 'Blob Analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 June 2025

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1

Ishida, T., Y. Ogawa, A. Kadokura, K. Hosokawa, and Y. Otsuka. "Direct observations of blob deformation during a substorm." Annales Geophysicae 33, no. 5 (2015): 525–30. http://dx.doi.org/10.5194/angeo-33-525-2015.

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Abstract. Ionospheric blobs are localized plasma density enhancements, which are mainly produced by the transportation process of plasma. To understand the deformation process of a blob, observations of plasma parameters with good spatial–temporal resolution are desirable. Thus, we conducted the European Incoherent Scatter radar observations with high-speed meridional scans (60–80 s) during October and December 2013, and observed the temporal evolution of a blob during a substorm on 4 December 2013. This paper is the first report of direct observations of blob deformation during a substorm. The blob deformation arose from an enhanced plasma flow shear during the substorm expansion phase, and then the blob split into two smaller-scale blobs, whose scale sizes were more than ~100 km in latitude. Our analysis indicates that the Kelvin–Helmholtz instability and dissociative recombination could have deformed the blob structure.

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Srinivasu, Srinivasu, Soundararajan Soundararajan, and Sakthishree Sakthishree. "Marine Object Recognition using Blob Analysis." International Journal of Computing Algorithm 5, no. 2 (2016): 97–98. http://dx.doi.org/10.20894/ijcoa.101.005.002.008.

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3

Carbary, J. F., K. Liou, A. T. Y. Lui, P. T. Newell, and C. I. Meng. "“Blob” analysis of auroral substorm dynamics." Journal of Geophysical Research: Space Physics 105, A7 (2000): 16083–91. http://dx.doi.org/10.1029/1999ja000210.

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4

Li, Teng, Yanzhe Xu, Teresa Wu, Jennifer R. Charlton, Kevin M. Bennett, and Firas Al-Hindawi. "BlobCUT: A Contrastive Learning Method to Support Small Blob Detection in Medical Imaging." Bioengineering 10, no. 12 (2023): 1372. http://dx.doi.org/10.3390/bioengineering10121372.

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Medical imaging-based biomarkers derived from small objects (e.g., cell nuclei) play a crucial role in medical applications. However, detecting and segmenting small objects (a.k.a. blobs) remains a challenging task. In this research, we propose a novel 3D small blob detector called BlobCUT. BlobCUT is an unpaired image-to-image (I2I) translation model that falls under the Contrastive Unpaired Translation paradigm. It employs a blob synthesis module to generate synthetic 3D blobs with corresponding masks. This is incorporated into the iterative model training as the ground truth. The I2I translation process is designed with two constraints: (1) a convexity consistency constraint that relies on Hessian analysis to preserve the geometric properties and (2) an intensity distribution consistency constraint based on Kullback-Leibler divergence to preserve the intensity distribution of blobs. BlobCUT learns the inherent noise distribution from the target noisy blob images and performs image translation from the noisy domain to the clean domain, effectively functioning as a denoising process to support blob identification. To validate the performance of BlobCUT, we evaluate it on a 3D simulated dataset of blobs and a 3D MRI dataset of mouse kidneys. We conduct a comparative analysis involving six state-of-the-art methods. Our findings reveal that BlobCUT exhibits superior performance and training efficiency, utilizing only 56.6% of the training time required by the state-of-the-art BlobDetGAN. This underscores the effectiveness of BlobCUT in accurately segmenting small blobs while achieving notable gains in training efficiency.

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Patel, Aeman Alijahan, and Rachna Y. Patil. "Diagnosis of Diabetic Retinopathy using Blob Analysis." International Journal of Computer Applications 183, no. 32 (2021): 8–11. http://dx.doi.org/10.5120/ijca2021921707.

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6

Yusuf, Muhammad Dede, RD Kusumanto, Yurni Oktarina, Tresna Dewi, and Pola Risma. "BLOB Analysis for Fruit Recognition and Detection." Computer Engineering and Applications Journal 7, no. 1 (2018): 25–36. http://dx.doi.org/10.18495/comengapp.v7i1.237.

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Robot application in agriculture can ease the farming process, especially as the harvesting robot for seasonal fruit that is available in a short time. The addition of "eye" as the image sensor is an important feature for a harvesting robot. Thanks to the increment of technology, the camera is getting smaller with better performance, and lower prices. The cheap sensors and components make the creation of cheap and effective robot possible. Image processing is necessary for object detection, and open source software is available now for this purpose. This paper proposes BLOB analysis for object detection of 5 fruits with different shapes and colors. The simulation results show that the proposed method is effective for object detection regardless the shapes, colors, and noises.

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Song, J. S., K. Maghsoudi, W. Li, E. Fox, J. Quackenbush, and X. Shirley Liu. "Microarray blob-defect removal improves array analysis." Bioinformatics 23, no. 8 (2007): 966–71. http://dx.doi.org/10.1093/bioinformatics/btm043.

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Couprie, Camille, Laurent Duval, Maxime Moreaud, Sophie Hénon, Mélinda Tebib, and Vincent Souchon. "BARCHAN: Blob Alignment for Robust CHromatographic ANalysis." Journal of Chromatography A 1484 (February 2017): 65–72. http://dx.doi.org/10.1016/j.chroma.2017.01.003.

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9

Saitoh, Machi, and Hiroshi Katsulai. "Detection of Blobs Using Variable Windows." Journal of Robotics and Mechatronics 7, no. 5 (1995): 404–9. http://dx.doi.org/10.20965/jrm.1995.p0404.

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A blob is a compact region in the image which is surrouded by a smoothly curved closed edge and, at the same time, is lighter or darker than the background. Many objects which are found in an image can be viewed as blobs. It is very important to quickly detect in an image the location of blobs for a wide range of applications of image analysis. In this paper, we propose a noniterative simple method of blob detection which is applicable to various forms of blobs by scanning an image with a size variable window, and does not require so much memory and time for computations because of its simplicity, and demonstrate its effectiveness through experiments.

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Petrovic, Vladimir, and Jelena Popovic-Bozovic. "A method for real-time memory efficient implementation of blob detection in large images." Serbian Journal of Electrical Engineering 14, no. 1 (2017): 67–84. http://dx.doi.org/10.2298/sjee1701067p.

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In this paper we propose a method for real-time blob detection in large images with low memory cost. The method is suitable for implementation on the specialized parallel hardware such as multi-core platforms, FPGA and ASIC. It uses parallelism to speed-up the blob detection. The input image is divided into blocks of equal sizes to which the maximally stable extremal regions (MSER) blob detector is applied in parallel. We propose the usage of multiresolution analysis for detection of large blobs which are not detected by processing the small blocks. This method can find its place in many applications such as medical imaging, text recognition, as well as video surveillance or wide area motion imagery (WAMI). We explored the possibilities of usage of detected blobs in the feature-based image alignment as well. When large images are processed, our approach is 10 to over 20 times more memory efficient than the state of the art hardware implementation of the MSER.

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11

Lia, Barry, and Jaime F. Olavarria. "The distribution of corticotectal projection neurons correlates with the interblob compartment in macaque striate cortex." Visual Neuroscience 13, no. 3 (1996): 461–66. http://dx.doi.org/10.1017/s0952523800008130.

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AbstractWhile much attention has been given to the correlation between cytochrome-oxidase (CO) compartments and patterns of cortico-cortical projections originating from supragranular layers in the striate cortex, little is known in this regard about patterns of cortico-subcortical projections originating from infragranular cortex. We studied the tangential distribution of the striate cortex neurons projecting to the superior colliculus and used two approaches to analyze the relationship of this distribution to the arrangement of CO “blobs.” First, chi-square analysis indicated that significantly fewer labeled neurons were found within the CO blob compartment than the number expected for a random distribution. Second, spatial cross-correlation analysis – which circumvents the inherent subjectivity of delineating blob boundaries – revealed an area around blob centers in which there was a decreased probability of encountering labeled cells. The size of this area compared well with that of our outlines of CO blobs. We conclude that corticotectal projection neurons in the striate cortex are distributed preferentially within the interblob compartment of the infragranular striate cortex. These results demonstrate that the spatial distribution of cortico-subcortical projection neurons within infragranular cortex can correlate with the CO architecture of the primary visual cortex.

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Daher, Zouheir, and Hassan Hajjdiab. "Cloud Storage Comparative Analysis Amazon Simple Storage vs. Microsoft Azure Blob Storage." International Journal of Machine Learning and Computing 8, no. 1 (2018): 85–89. http://dx.doi.org/10.18178/ijmlc.2018.8.1.668.

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Bolton, E. W., F. H. Busse, and R. M. Clever. "Oscillatory instabilities of convection rolls at intermediate Prandtl numbers." Journal of Fluid Mechanics 164 (March 1986): 469–85. http://dx.doi.org/10.1017/s0022112086002641.

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The analysis of the instabilities of convection rolls in a fluid layer heated from below with no-slip boundaries exhibits a close competition between various oscillatory modes in the range 2 [lsim ] P [lsim ] 12 of the Prandtl number P. In addition to the even-oscillatory instability known from earlier work two new instabilities have been found, each of which is responsible for a small section of the stability boundary of steady rolls. The most interesting property of the new instabilities is their close relationship to the hot-blob oscillations known from experimental studies of convection. In the lower half of the Prandtl-number range considered the B02-mode dominates, which is characterized by two blobs each of slightly hotter and colder fluid circulating around in the convection roll in a spatially and time-periodic fashion. At higher Prandtl numbers the BE 1-mode dominates, which possesses one hot blob (and one cold blob) circulating with the convection velocity. Just outside the stability boundary there exist other growing modes exhibiting three or four blobs which may be observable in experiments.

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Zhang, Zeng Ping, and Shu Hua Li. "Research of Video Tracking Algorithm Based on the Blob Analysis." Advanced Materials Research 383-390 (November 2011): 1185–89. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.1185.

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To the video that contains the target, a method is proposed to create the background model based on the mixed Gauss. And the target locating method based on the blob analysis and blob filtering, the anti-noise ability and filter robustness of tracking is improved. The kalman filter and the particle filter are separately used to pass and update the foreground target’s posterior probability distribution. Finally the kalman filter and the particle filter's are compared and that builds the foundation of the further development.

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15

Santi Wahyuni, Febriana. "PENERAPAN BLOB (BINARY LARGE OBJECT) ANALYSIS PADA SISTEM PENGENALAN RAMBU-RAMBU LALU LINTAS." Jurnal Mnemonic 1, no. 2 (2019): 62–66. http://dx.doi.org/10.36040/mnemonic.v1i2.40.

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Blob analysis merupakan satu metode paling dasar dalam pengolahan citra dan visi computer, yang bertujuan untuk menganalisis fitur bentuk suatu objek. Pada metode ini akan diperoleh beberapa ukuran dari properti yang dimiliki oleh suatu citra. Adapun properti-properti yang di ukur adalah luas (area), bounding box, diameter, keliling (perimeter), dan titik ekstrema. Dalam system pengenalan rambu-rambu lalu lintas ini, analisa blob merupakan salah satu tahapan dalam tahap deteksi selain deteksi warna. Dari tahap pengujian diperoleh hasil prosentase keberhasilan dari analisis blob dalam mengenali bentuk segiempat sebesar 33,33%, bentuk lingkaran sebesar 71,43% dan bentuk diamond sebesar 100%.

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Gorbachev, I. N., R. A. Tomakova, and S. V. Korobkov. "Methods and algorithms for identifying special points in images obtained from an onboard photo video recorder of an unmanned aerial vehicle." Proceedings of the Southwest State University. Series: IT Management, Computer Science, Computer Engineering. Medical Equipment Engineering 15, no. 1 (2025): 91–116. https://doi.org/10.21869/2223-1536-2025-15-1-91-116.

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The purpose of the research is to develop methods for controlling unmanned aerial vehicles based on the analysis of data coming from a video stream.Methods. An unmanned aerial vehicle can lose contact with the satellite navigation system, so the task of ensuring its orientation using an onboard photo video recorder with onboard data processing becomes relevant. For this purpose, special points on the terrain are used, the identification of which in the picture allows restoring the orientation of the aircraft. To search for special points of the blob type in the picture, a method is proposed for transforming the original image into a criterion image, after threshold processing of which the coordinates of the blobs are obtained. A method has been developed for transforming the original image into a criterion image, which consists in determining correlation images. For each correlation image, a scalar blob identification criterion is determined, which allows determining the coordinates of a special point in pictures obtained from an onboard photo video recorder.Results. To improve the accuracy of determining the coordinates of blobs in pictures, an aggregated blob of three special points was used. An algorithm for two-stage identification of coordinates of an aggregated blob is investigated. At the first stage, the coordinates of special points closest to the coordinates of the vertices of the aggregated blob are determined, and at the second stage, the coordinates of the vertices of the triangle whose center of gravity is closest to the center of gravity of the aggregated blob are determined. The algorithms for searching for special points have shown their efficiency at a high level of interference modeled in the image by means of Gaussian noise, as well as interference associated with the deviation of the aircraft from the specified course.Conclusion. The formation of an aggregated blob with subsequent multi-stage identification allows for increasing the accuracy of determining its coordinates, and also makes it possible to record the deviation from the course of the aircraft in the area of two adjacent images and introduce appropriate corrections into the navigation system.

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Bright, David S. "Selection of Em Analysis Points Using the Euclidian Distance Map." Proceedings, annual meeting, Electron Microscopy Society of America 48, no. 1 (1990): 534–35. http://dx.doi.org/10.1017/s0424820100181427.

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An image with morphological information, such as a backscatter electron image, can be acquired quickly to provide points for spectroscopic analyses that usually take more instrument time. It is desirable to have the analysis points be in the interior of the particles or objects of interest. The Euclidian distance map is applied directly to this problem to maximize the distance of the analysis sites from any part of the object perimeter.The first step in using an electron image to select points for spectroscopic analysis is often to make a binary image of the original, in which picture elements (pixels) corresponding to particles, or the crystalline phase of interest, for example, are white, while all other pixels, corresponding to background, are black. The second step is to select analysis points for each particle or ‘blob’ (group of contiguous pixels) in the binary image. The centroid or center of area (at tips of arrows, Fig. 1) is used when one analysis point is desired and the blob is sufficiently convex or straight (upper left arrow, Fig. 1). However, if the blobs are curved or have indentations or holes, the centroid may actually lie in the background rather than in the area to be analyzed (middle and lower arrows, Fig. 1).

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18

Indrabayu, Indrabayu, Rahmat Hardian Putra, Ingrid Nurtanio, Intan Sari Areni, and Anugrayani Bustamin. "Blob adaptation through frames analysis for dynamic fire detection." Bulletin of Electrical Engineering and Informatics 9, no. 5 (2020): 2189–97. http://dx.doi.org/10.11591/eei.v9i5.2622.

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This study was aiming at helping visually impaired people to detect and estimate the fire distance. Blind people had difficulty knowing the existence of fire at a safe distance; hence the possibility of burning could occur. The color models and blob analysis methods were used to detect the presence of fire in the blind path. Before the fire detection stage, the cascade of the HSV and RGB color models was applied to segment the reddish fire color. The size and shape of a dynamic fire were the parameters used in this paper to distinguish fire from non-fire objects. Changes in the area of the fire object obtained at the Blob analysis stage per 10 frames were the main contributions and novelty in this paper. After the fire is detected, the calculation of the fire distance to a blind person was completed using a pinhole model. This research used 35 data videos with a resolution of 480x640 pixels. The results showed that the fire detection system and the distance estimation achieved an accuracy of 88.86% and the MSE of 0.0358, respectively.

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Indrabayu, Hardian Putra Rahmat, Nurtanio Ingrid, Sari Areni Intan, and Bustamin Anugrayani. "Blob adaptation through frames analysis for dynamic fire detection." Bulletin of Electrical Engineering and Informatics 9, no. 5 (2020): 2189–97. https://doi.org/10.11591/eei.v9i5.2622.

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This study was aiming at helping visually impaired people to detect and estimate the fire distance. Blind people had difficulty knowing the existence of fire at a safe distance; hence the possibility of burning could occur. The color models and blob analysis methods were used to detect the presence of fire in the blind path. Before the fire detection stage, the cascade of the HSV and RGB color models was applied to segment the reddish fire color. The size and shape of a dynamic fire were the parameters used in this paper to distinguish fire from non-fire objects. Changes in the area of the fire object obtained at the Blob analysis stage per 10 frames were the main contributions and novelty in this paper. After the fire is detected, the calculation of the fire distance to a blind person was completed using a pinhole model. This research used 35 data videos with a resolution of 480x640 pixels. The results showed that the fire detection system and the distance estimation achieved an accuracy of 88.86% and the MSE of 0.0358, respectively.

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20

Alex, Prince, Ruggero Barni, Hector Eduardo Roman, and Claudia Riccardi. "Intermittent structures and quasi-stationary equilibrium in a simple magnetized torus in open field line configuration." Journal of Physics Communications 6, no. 1 (2022): 015010. http://dx.doi.org/10.1088/2399-6528/ac4d17.

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Abstract A steady regime dominated by intermittent blob and hole structures is identified in the plasma state of a simple magnetized torus by achieving a quasi-stationary equilibrium using an open magnetic field line configuration. The open helical field line configuration is characterized by a connection length, L c = 2 a B φ B z ≳ 1750 cm, and pitch ratio, r B = B z B φ ≲ 0.01 . This is realized by superposing a vertical magnetic fied, B z , to the toroidal field, B φ , and the regime is achieved for B z ≤ 0.4 mT. The combined effect of plasma rotation, arising from a substantial radial electric field, together with an open field line, results in vertically elongated plasma profile and an asymmetric sheared poloidal flow. The analysis shows the existence of density fluctuations exhibiting universal statistical properties, dominated by non-Gaussian blob events in the edge region and holes in the core plasma, separated by a region ascribed as blob birth zone corresponding to a velocity shear layer. Two-dimensional conditional averaging analyses of fluctuations indicate that blobs form in the sheared layer, when the leading edge of an elongated coherent structure breaks off by differential stretching exerted by the background fluctuating field. Convection of this isolated blob out of the contour corresponding to the maximum radial electric field in the low field side, leads to its ejection while holes move along the same contour driven back into the main plasma. The corresponding potential structure shows counter-rotating E × B velocity field within oppositely charged structures, where the embedded electric field is consistent with the observed structure propagation. A comparison with cross-correlation analysis yields a similar conclusion except for a slight overestimation of the structure size and lifetime.

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Piątkowski, Tomasz. "Identification of the object motion trajectory in a digital image using the Kalman filter." Journal of Automation, Electronics and Electrical Engineering 5, no. 3 (2024): 31–45. http://dx.doi.org/10.24136/jaeee.2023.009.

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The paper concerns identification of the object motion trajectories in a digital image. An image analysis procedure was used consisting of two methods: BLOB identification and Kalman filter. BLOB identification is the superior method, and the Kalman filter is an alternative one, used to determine the motion trajectories only in the event of incorrect BLOB identification. Data from the correct BLOB identification are used on an ongoing basis in the process of training the Kalman filter. In this way, the filter becomes a model of a physical object that allows predicting the future state based on the object's current behaviour. The use of two complementary image analysis methods allows to determine the motion trajectories of the object's characteristic points in conditions of uneven scene lighting. The effectiveness of the method was confirmed in experimental rests.

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22

Di Ruberto, Cecilia, Andrea Loddo, and Giovanni Puglisi. "Blob Detection and Deep Learning for Leukemic Blood Image Analysis." Applied Sciences 10, no. 3 (2020): 1176. http://dx.doi.org/10.3390/app10031176.

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In microscopy, laboratory tests make use of cell counters or flow cytometers to perform tests on blood cells, like the complete blood count, rapidly. However, a manual blood smear examination is still needed to verify the counter results and to monitor patients under therapy. Moreover, the manual inspection permits the description of the cells’ appearance, as well as any abnormalities. Unfortunately, manual analysis is long and tedious, and its result can be subjective and error-prone. Nevertheless, using image processing techniques, it is possible to automate the entire workflow, both reducing the operators’ workload and improving the diagnosis results. In this paper, we propose a novel method for recognizing white blood cells from microscopic blood images and classify them as healthy or affected by leukemia. The presented system is tested on public datasets for leukemia detection, the SMC-IDB, the IUMS-IDB, and the ALL-IDB. The results are promising, achieving 100% accuracy for the first two datasets and 99.7% for the ALL-IDB in white cells detection and 94.1% in leukemia classification, outperforming the state-of-the-art.

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SUGITA, Satoru, Masatoshi YAGI, Sanae I. ITOH, and Kimitaka ITOH. "Propagation Velocity Analysis of a Single Blob in the SOL." Plasma and Fusion Research 3 (2008): 040. http://dx.doi.org/10.1585/pfr.3.040.

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Gaikwad, Sonal Dattatray. "Segmentation of WBCs using HSV Saturation and Blob Analysis Technique." International Journal for Research in Applied Science and Engineering Technology 7, no. 4 (2019): 2290–92. http://dx.doi.org/10.22214/ijraset.2019.4414.

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Kawulok, Michal. "Energy-based blob analysis for improving precision of skin segmentation." Multimedia Tools and Applications 49, no. 3 (2010): 463–81. http://dx.doi.org/10.1007/s11042-009-0444-z.

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Offeddu, N., C. Wüthrich, W. Han, et al. "Analysis techniques for blob properties from gas puff imaging data." Review of Scientific Instruments 94, no. 3 (2023): 033512. http://dx.doi.org/10.1063/5.0133506.

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Filamentary structures, also known as blobs, are a prominent feature of turbulence and transport at the edge of magnetically confined plasmas. They cause cross-field particle and energy transport and are, therefore, of interest in tokamak physics and, more generally, nuclear fusion research. Several experimental techniques have been developed to study their properties. Among these, measurements are routinely performed with stationary probes, passive imaging, and, in more recent years, Gas Puff Imaging (GPI). In this work, we present different analysis techniques developed and used on 2D data from the suite of GPI diagnostics in the Tokamak à Configuration Variable, featuring different temporal and spatial resolutions. Although specifically developed to be used on GPI data, these techniques can be employed to analyze 2D turbulence data presenting intermittent, coherent structures. We focus on size, velocity, and appearance frequency evaluation with, among other methods, conditional averaging sampling, individual structure tracking, and a recently developed machine learning algorithm. We describe in detail the implementation of these techniques, compare them against each other, and comment on the scenarios to which these techniques are best applied and on the requirements that the data must fulfill in order to yield meaningful results.

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Areni, Intan Sari, Indrabayu Amirullah, Ingrid Nurtanio, Anugrayani Bustamin, and Ahmad Rifaldi. "Sistem Deteksi Lubang pada Pedesterian dengan Teknik Pengolahan Citra." Jurnal Penelitian Enjiniring 23, no. 2 (2019): 117–20. http://dx.doi.org/10.25042/jpe.112019.04.

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Pothole Detection System on Pedesterian using Image Processing Techniques. The pedestrian areas in Indonesia are still far from optimal in facilitating the users or the pedestrians. Potholed pedestrian areas are found in many parts of the street. This issue can harm pedestrians, especially blind people. For this reason, research has been carried out to create a system that can detect and estimate hole distances by processing images using mono cameras that can help blind people. The methods used to detect holes are the Threshold + Blob Analysis method and the HSV method. The obtained results indicate the level of accuracy of hole detection using the Threshold + Blob Analysis method is better than the HSV method. The average accuracy level of Threshold + Blob Analysis is 88.91%, while for the HSV method is 86.82%.

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Ikasari, Ines Hediani, Resti Amalia, and Perani Rosyani. "Segmentasi Citra Bunga Menggunakan Blob Analisis." Building of Informatics, Technology and Science (BITS) 3, no. 3 (2021): 228–34. http://dx.doi.org/10.47065/bits.v3i3.1050.

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Content Based Image Retrieval (CBIR) for image segmentation is a concern this year, especially in the development of computer vision. The object discussed in this study is about interest, which uses a dataset from ImageCLEF2017 by taking 8 flower samples. Image of flowers in the dataset is still a lot of noise such as the initial background behind objects such as leaves, tree trunks or others. So we need a method to eliminate the noise, this method for cleaning noise is done by color clusters using the K-means method. By color clustering using K-Means and using color clusters k=2,3,4,and5. After that, a morphological process is carried out in order to obtain a clean area so that it can be compared with the original image and the Blob values formed. Blob analysis is calculated after the process of cleaning the noise is done in order to get the best value in the process of recognition of images with objects of interest. The results of the segmentation process that have been done are the highest MSE and RMSE values are at k-means results with k=4, while for PNSR are at k=2, and for the lowest MSE and RMSE values are at k=5, while the lowest PNSR is at k=4

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Ibrahim, Furkan Ince, Socarras-Garzon Manuel, and Yang Tae-Cheon. "Hand Mouse: Real Time Hand Motion Detection System Based on Analysis of Finger Blobs." International Journal of Digital Content Technology and its Applications (JDCTA) 4, no. 2 (2010): 40–56. https://doi.org/10.4156/jdcta.vol4.issue2.5.

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Hand detection is a fundamental step in many practical applications as gesture recognition, video surveillance, and multimodal machine interface and so on. The aim of this paper is to present the methodology for hand detection and propose the hand motion detection method. Skin color is used to segment the hand region from background and hand blob is extracted from the segmented finger blobs. Analysis of finger blobs gives us the location of hand even when hand and head blobs are visible in the same image. In this paper, we propose a fast, computationally inexpensive solution which uses any type of computer video camera to control a cursor through hand movements and gesticulations. The design and evaluation phases are presented in detail. We have performed extensive experiments and achieve very encouraging results. Finally, we discuss the effectiveness of the proposed method through several experimental results.

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Roy, Soumya, Durgesh Tripathi, Vishal Upendran, et al. "X-class Flare on 2023 December 31 Observed by the Solar Ultraviolet Imaging Telescope on Board Aditya-L1." Astrophysical Journal Letters 983, no. 1 (2025): L6. https://doi.org/10.3847/2041-8213/adc387.

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Abstract We present the multiwavelength study of the ejection of a plasma blob from the limb flare SOL2023-12-31T21:36:00 from NOAA 13536 observed by the Solar Ultraviolet Imaging Telescope (SUIT) on board Aditya-L1. We use SUIT observations along with those from the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory and Spectrometer/Telescope for Imaging X-rays (STIX) on board Solar Orbiter to infer the kinematics and thermal nature of the ejected blob and its connection to the associated flare. The observations show that the flare was comprised of two eruptions. The blob was ejected during the first eruption and later accelerated to velocities over 1500 km s−1 measured at a maximum projected height of ∼178 Mm from the Sun’s surface. The acceleration of the ejected plasma blob is cotemporal with the bursty appearance of the hard X-ray light curve recorded by STIX. Radio spectrogram observations from STEREO-A/WAVES and RSTN reveal type III bursts at the same time, indicative of magnetic reconnection. DEM analysis using AIA observations suggests the plasma blob is comprised of cooler and denser plasma in comparison to the ambient corona. To the best of our knowledge, this is the first observation of such a plasma blob in the near-ultraviolet providing crucial measurements for eruption thermodynamics.

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Jo, Ahra, Jeong-Sik Park, Yong-Ho Seo, and Gil-Jin Jang. "Performance Improvement of Human Detection in Thermal Images using Principal Component Analysis and Blob Clustering." Journal of the Institute of Webcasting, Internet and Telecommunication 13, no. 2 (2013): 157–63. http://dx.doi.org/10.7236/jiibc.2013.13.2.157.

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Bastin, P., T. J. Pullen, T. Sherwin, and K. Gull. "Protein transport and flagellum assembly dynamics revealed by analysis of the paralysed trypanosome mutant snl-1." Journal of Cell Science 112, no. 21 (1999): 3769–77. http://dx.doi.org/10.1242/jcs.112.21.3769.

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The paraflagellar rod (PFR) of Trypanosoma brucei is a large, complex, intraflagellar structure that represents an excellent system in which to study flagellum assembly. Molecular ablation of one of its major constituents, the PFRA protein, in the snl-1 mutant causes considerable alteration of the PFR structure, leading to cell paralysis. Mutant trypanosomes sedimented to the bottom of the flask rather than staying in suspension but divided at a rate close to that of wild-type cells. This phenotype was complemented by transformation of snl-1 with a plasmid overexpressing an epitope-tagged copy of the PFRA gene. In the snl-1 mutant, other PFR proteins such as the second major constituent, PFRC, accumulated at the distal tip of the growing flagellum, forming a large dilation or ‘blob’. This was not assembled as filaments and was removed by detergent-extraction. Axonemal growth and structure was unmodified in the snl-1 mutant and the blob was present only at the tip of the new flagellum. Strikingly, the blob of unassembled material was shifted towards the base of the flagellum after cell division and was not detectable when the daughter cell started to produce a new flagellum in the next cell cycle. The dynamics of blob formation and regression are likely indicators of anterograde and retrograde transport systems operating in the flagellum. In this respect, the accumulation of unassembled PFR precursors in the flagellum shows interesting similarities with axonemal mutants in other systems, illustrating transport of components of a flagellar structure during both flagellum assembly and maintenance. Observation of PFR components indicate that these are likely to be regulated and modulated throughout the cell cycle.

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TJ, Mr GOWTHAM. "ELECTION RESULT PREDICTION." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 06 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem36223.

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This study utilizes Text Blob for sentiment analysis of social media and news data to predict election results. By analyzing sentiment polarity, a comprehensive understanding of public opinion towards political entities is obtained. Machine learning algorithms are employed to build predictive models using historical election data. Results demonstrate the effectiveness of sentiment analysis in enhancing prediction accuracy compared to traditional methods. This research has implications for political campaigns and policymakers in gauging public sentiment and anticipating electoral outcomes. Keywords— Text Blob, sentiment analysis, election prediction, social media, machine learning.

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Müller, Maja-Lisa. "Blobs, Slime, and Fungi. The Queer Potential of a Mediamycology." REGAC - Revista de Estudios Globales y Arte Contempor�neo 8, no. 1 (2022): 231–49. http://dx.doi.org/10.1344/regac2022.8.41423.

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This article wants to establish the blob and with it other amorphous structures not only as a symptom for life in networked times, but also as a way of thinking with blobs in queering ontological, biological and disciplinary spheres. In their emergent state, they are quasi-objects in nucleo and ontological beings in the process of unfolding, of spreading and coming into existence. In its amorphous form the blob questions scientific, philosophical as well as aesthetic categories and shall therefore be explored from these different perspectives. In a comparative analysis of art works as well as texts from different scientific disciplines such as biology and anthropology, amorph objects reveal their world-building and connecting abilities across species and spheres. They can be understood as natural media of linking and cultivation. Drawing from queer theory the abject culture of these phenomena asks for a reevaluation of these attributions and towards an appropriation of the dangerous qualities ascribed to slime and fungi.

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., Sutrisno, Imam Cholissodin, Rina Christanti, Candra Dewi, and Nurul Hidayat. "Segmentasi Kendaraan Menggunakan Improve Blob Analysis (BA) Pada Video Lalu Lintas." Jurnal Teknologi Informasi dan Ilmu Komputer 2, no. 1 (2015): 67. http://dx.doi.org/10.25126/jtiik.201521132.

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Duan, Yong, and Jian-Guo Liu. "Convergence analysis of the vortex blob method for the $b$-equation." Discrete & Continuous Dynamical Systems - A 34, no. 5 (2014): 1995–2011. http://dx.doi.org/10.3934/dcds.2014.34.1995.

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Reza Rahmani, Amir, Maša Prodanović, Steven L. Bryant, and Chun Huh. "Quasi-static analysis of a ferrofluid blob in a capillary tube." Journal of Applied Physics 111, no. 7 (2012): 074901. http://dx.doi.org/10.1063/1.3697894.

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Hou, Thomas Y. "Convergence of a Variable Blob Vortex Method for the Euler and Navier–Stokes Equations." SIAM Journal on Numerical Analysis 27, no. 6 (1990): 1387–404. http://dx.doi.org/10.1137/0727080.

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Mari, Simone, Giovanni Bucci, Fabrizio Ciancetta, Edoardo Fiorucci, and Andrea Fioravanti. "Automated Quality Control of Cleaning Processes in Automotive Components Using Blob Analysis." Sensors 25, no. 9 (2025): 2710. https://doi.org/10.3390/s25092710.

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This study presents an automated computer vision system for assessing the cleanliness of plastic mirror caps used in the automotive industry after a washing process. These components are highly visible and require optimal surface conditions prior to painting, making the detection of residual contaminants critical for quality assurance. The system acquires high-resolution monochrome images under various lighting configurations, including natural light and infrared (IR) at 850 nm and 940 nm, with different angles of incidence. Four blob detection algorithms—adaptive thresholding, Laplacian of Gaussian (LoG), Difference of Gaussians (DoG), and Determinant of Hessian (DoH)—were implemented and evaluated based on their ability to detect surface impurities. Performance was assessed by comparing the total detected blob area before and after the cleaning process, providing a proxy for both sensitivity and false positive rate. Among the tested methods, adaptive thresholding under 30° natural light produced the best results, with a statistically significant z-score of +2.05 in the pre-wash phase and reduced false detections in post-wash conditions. The LoG and DoG methods were more prone to spurious detections, while DoH demonstrated intermediate performance but struggled with reflective surfaces. The proposed approach offers a cost-effective and scalable solution for real-time quality control in industrial environments, with the potential to improve process reliability and reduce waste due to surface defects.

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Barrow, Harry G., Alistair J. Bray, and Julian M. L. Budd. "A Self-Organizing Model of “Color Blob” Formation." Neural Computation 8, no. 7 (1996): 1427–48. http://dx.doi.org/10.1162/neco.1996.8.7.1427.

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This paper explores the possibility that the formation of color blobs in primate striate cortex can be partly explained through the process of activity-based self-organization. We present a simulation of a highly simplified model of visual processing along the parvocellular pathway, that combines precortical color processing, excitatory and inhibitory cortical interactions, and Hebbian learning. The model self-organizes in response to natural color images and develops islands of unoriented, color-selective cells within a sea of contrast-sensitive, orientation-selective cells. By way of understanding this topography, a principal component analysis of the color inputs presented to the network reveals that the optimal linear coding of these inputs keeps color information and contrast information separate.

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Herenz, Edmund Christian, Matthew Hayes та Claudia Scarlata. "Deciphering the Lyman α blob 1 with deep MUSE observations". Astronomy & Astrophysics 642 (жовтень 2020): A55. http://dx.doi.org/10.1051/0004-6361/202037464.

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Context. Lyman α blobs (LABs) are large-scale radio-quiet Lyman α (Lyα) nebula at high-z that occur predominantly in overdense proto-cluster regions. In particular, there is the prototypical SSA22a-LAB1 at z = 3.1, which has become an observational reference for LABs across the electromagnetic spectrum. Aims. We want to understand the powering mechanisms that drive the LAB so that we may gain empirical insights into the galaxy-formation processes within a rare dense environment at high-z. Thus, we need to infer the distribution, the dynamics, and the ionisation state of LAB 1’s Lyα emitting gas. Methods. LAB 1 was observed for 17.2 h with the VLT/MUSE integral-field spectrograph. We produced optimally extracted narrow band images, in Lyαλ1216, He IIλ1640, and we tried to detect C IVλ1549 emission. By utilising a moment-based analysis, we mapped the kinematics and the line profile characteristics of the blob. We also linked the inferences from the line profile analysis to previous results from imaging polarimetry. Results. We map Lyα emission from the blob down to surface-brightness limits of ≈6 × 10−19 erg s−1 cm−2 arcsec−2. At this depth, we reveal a bridge between LAB 1 and its northern neighbour LAB 8, as well as a shell-like filament towards the south of LAB 1. The complexity and morphology of the Lyα profile vary strongly throughout the blob. Despite the complexity, we find a coherent large-scale east-west velocity gradient of ∼1000 km s−1 that is aligned perpendicular to the major axis of the blob. Moreover, we observe a negative correlation of Lyα polarisation fraction with Lyα line width and a positive correlation with absolute line-of-sight velocity. Finally, we reveal He II emission in three distinct regions within the blob, however, we can only provide upper limits for C IV. Conclusions. Various gas excitation mechanisms are at play in LAB 1: ionising radiation and feedback effects dominate near the embedded galaxies, while Lyα scattering contributes at larger distances. However, He II/Lyα ratios combined with upper limits on C IV/Lyα are not able to discriminate between active galactic nucleus ionisation and feedback- driven shocks. The alignment of the angular momentum vector parallel to the morphological principal axis appears to be at odds with the predicted norm for high-mass halos, but this most likely reflects that LAB 1 resides at a node of multiple intersecting filaments of the cosmic web. LAB 1 can thus be thought of as a progenitor of a present-day massive elliptical within a galaxy cluster.

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SHI, Xiao-cheng, Li-chao HAO, Wei ZHANG, and Di WU. "Underwater targets extraction method based on Blob analysis and Bayesian design-making." Journal of Computer Applications 32, no. 11 (2013): 3214–17. http://dx.doi.org/10.3724/sp.j.1087.2012.03214.

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Leitner, R., H. Mairer, and A. Kercek. "Real-time classification of polymers with NIR spectral imaging and blob analysis." Real-Time Imaging 9, no. 4 (2003): 245–51. http://dx.doi.org/10.1016/j.rti.2003.09.016.

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Abdullah, Hadeel N., and Nuha H. Abdulghafoor. "Automatic Objects Detection and Tracking Using FPCP, Blob Analysis and Kalman Filter." Engineering and Technology Journal 38, no. 2A (2020): 246–54. http://dx.doi.org/10.30684/etj.v38i2a.314.

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Object detection and tracking are key mission in computer visibility applications, including civil or military surveillance systems. However, there are major challenges that have an effective role in the accuracy of detection and tracking such as the ability of the system to track the target and the response speed of the system in different environments as well as the presence of noise in the captured video sequence. In this proposed work, a new algorithm to detect moving objects from video data is designed by the Fast Principle Component Purist (FPCP). Then, we used an ideal filter that performs well to reduce noise through the morphological filter. The Blob analysis is used to add smoothness to the spatial identification of objects and their areas, and finally, the detected object is tracked by Kalman Filter. The applied examples demonstrated the efficiency and capability of the proposed system for noise removal, detection accuracy and tracking.

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Piao, Jingchun, and Hyunchul Shin. "Robust hypothesis generation method using binary blob analysis for multi-lane detection." IET Image Processing 11, no. 12 (2017): 1210–18. http://dx.doi.org/10.1049/iet-ipr.2016.0506.

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Corapcioglu, M. Yavuz, Sunhee Yoon, and Sabina Chowdhury. "Pore-Scale Analysis of NAPL Blob Dissolution and Mobilization in Porous Media." Transport in Porous Media 79, no. 3 (2009): 419–42. http://dx.doi.org/10.1007/s11242-008-9331-8.

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Putra, Arief Bramanto Wicaksono, Mirza Rafdi Rosada, and Achmad Fanany Onnilita Gaffar. "PROTOTYPE REGION OF INTEREST (ROI) CITRA WAJAH MANUSIA BERBASIS BINARY LARGE OBJECT (BLOB) ANALYSIS." Dinamika Rekayasa 16, no. 2 (2020): 83. http://dx.doi.org/10.20884/1.dr.2020.16.2.285.

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<p>Setiap manusia memiliki identitasnya masing-masing, dan tidak akan sama satu identitas seseorang dengan identitas lainnya. Biometrik suatu wajah tidak akan sama dengan wajah lainnya, oleh karena itu dirancang suatu <em>prototype </em>pengenalan identitas ciri wajah pada wilayah-wilayah tertentu atau <em>Region of Interest </em>(ROI). ROI yang digunakan merupakan biometrik-biometrik unik yang terdapat pada wajah. Untuk mendapatkan ROI, proses segmentasi yang digunakan diantaranya adalah: Morfologi, <em>Flood fill Algorithm </em>dan <em>Tresholding. </em>Kemudian dengan menggunakan <em>BLOB Analysis</em> jumlah area dan nilai piksel yang terdapat pada ROI yang telah tersegmentasi akan dijadikan sebagai ekstraksi ciri pengenalan yang kemudian akan teridentifikasi menggunakan pendekatan <em>Euclidean distance</em>. ROI yang diperoleh dari ekstraksi menggunakan <em>BLOB analysis</em> mencakup 6 sampai 9 area biometrik wajah seperti alis, mata, hidung, mulut dan telinga. Hasil performansi dari identifikasi kemiripan wajah menggunakan 3 data wajah dengan 5 data sampel berbeda pada masing-masing wajah adalah 33,3%.</p>

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Nevil, Gajera, Chanchad Kishan, and Vora Sneh. "Twitter Sentiment Analysis with Textblob." International Journal of Innovative Science and Research Technology 7, no. 11 (2022): 761–66. https://doi.org/10.5281/zenodo.7392678.

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In the World, many social media sites exist like Twitter, Instagram, Facebook, Snapchat, etc. and data posted by people on these social media sites are increasing quickly that containing audio, video, text, and images. People use this site to share their thoughts and opinion and sometimes share their opinion and thoughts towards any company. For this, we have chosen twitter and applied sentiment analysis. In this paper, we discuss a method of data extraction through API, data cleaning, and use text blob python library for sentiment analysis.

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N. Hattarge, Shivlingappa. "SENTIMENT-BASED FEEDBACK ANALYSIS SYSTEM." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem04086.

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Abstract - Feedback analysis is important to know the satisfaction of the user, improve service and take decision. A Sentiment Based Feedback Analysis System which uses NLP (Natural Language Processing) techniques to classify feedback into positives, neutral and negative is proposed. The system is developed in Django, uses the MySQL as database and Text-Blob and Vader as sentiment libraries in Python. An admin dashboard allows visualization and filtering of sentiment trends for informed strategic academic or service decisions. Key Words: Sentiment Analysis, Feedback System, TextBlob, Vader, Django, Natural Language Processing (NLP).

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Murawwat, Sadia, Armish Qureshi, Saleha Ahmad, and Yousaira Shahid. "Weed Detection Using SVMs." Engineering, Technology & Applied Science Research 8, no. 1 (2018): 2412–16. https://doi.org/10.5281/zenodo.1207236.

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The major concern in Pakistani agriculture is the reduction of growing weed. This research aims to provide a weed detection tool for future agri-robots. The weed detection tool incorporates the use of machine-learning procedure explicitly implementing Support Vector Machines (SVMs) and blob analysis for the effective classification of crop and weed. Weed revealing is based on characteristic features i.e. red green blue (RGB) components which differentiate soil and plant. Morphological features—centroidand length aid to distinguish shape of crop and weed leaves. Following feature extraction, the positive and negative margins are separated by a hyper-plane. The separating hyper-plane acts as the decision surface. Sample input consists of multiple digital field images of carrot crops. Training samples of seventy two images are taken. Accuracy of the outcomes discloses that SVM and blob analysis attain above 50-95% accuracy.<em>Abstract</em>—The major concern in Pakistani agriculture is the reduction of growing weed. This research aims to provide a weed detection tool for future agri-robots. The weed detection tool incorporates the use of machine-learning procedure explicitly implementing Support Vector Machines (SVMs) and blob analysis for the effective classification of crop and weed. Weed revealing is based on characteristic features i.e. red green blue (RGB) components which differentiate soil and plant. Morphological features—centroidand length aid to distinguish shape of crop and weed leaves. Following feature extraction, the positive and negative margins are separated by a hyper-plane. The separating hyper-plane acts as the decision surface. Sample input consists of multiple digital field images of carrot crops. Training samples of seventy two images are taken. Accuracy of the outcomes discloses that SVM and blob analysis attain above 50-95% accuracy.

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