Relevant bibliographies by topics / Accumulated histogram

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Academic literature on the topic 'Accumulated histogram'

Author: Grafiati
Published: 3 June 2025
Last updated: 23 June 2025

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Journal articles on the topic "Accumulated histogram"

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Han, Yu, Ling Luo, Bin Xie, and Chen Xu. "Nonparametric histogram segmentation-based automatic detection of yarns." Textile Research Journal 90, no. 11-12 (2019): 1326–41. http://dx.doi.org/10.1177/0040517519890212.

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Detection of yarns in fabric images is a basic task in real-time monitoring in fabric production processes since it relates to yarn density and fabric structure estimation. In this paper, a new detection method is proposed that can automatically and efficiently estimate the locations as well as the numbers of both weft and warp yarn in fabric images. The method has three sequential phases. First, the modulus of discrete partial derivatives at each pixel is projected onto the weft and warp directions to generate the accumulated histograms. Second, for each histogram, a monotone hypothesis of a nonparametric statistical approach is applied to segment the histogram. Third, according to the segmentation result, the locations of each weft and warp yarn are adaptively determined, while the fabric structure is also obtained. Numerical results demonstrate that, compared with classical yarn detection methods, which are based on image smoothing, the proposed method can estimate yarn locations and fabric structures with more accuracy, but also reduce the influence of yarn hairiness.
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Bright, David S. "Software Tools for Examination of Microanalytical Images." Proceedings, annual meeting, Electron Microscopy Society of America 48, no. 2 (1990): 116–17. http://dx.doi.org/10.1017/s042482010013417x.

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Image processing for enhancement and interpretation is a powerful tool for microscopy and microanalysis. Digital images are arrays of picture elements or pixels each having a coordinate (location) and a value. Two dimensional arrays with single intensity value (monochrome) or triple intensity values (color) pixels are in common use. Software tools and techniques are now available for desk top computers at reasonable cost that allow visualization of higher dimensional arrays and multivalued pixels. The following examples illustrate the application of these tools to microanalysis.Short image sequences (movies) are useful for showing dynamic effects such as the drift of an electron microscope stage with time or the interior of a sample eroded by sputtering on an ion microscope.The values of the pixels of registered images or x-ray maps can be accumulated in a multidimensional histogram (Concentration Histogram Image or CHI). The number of registered maps determines the dimensionality of the histogram.
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Srikote, Gatesakda, and Anupap Meesomboon. "Face Recognition Performance Improvement Using Derivative of Accumulated Absolute Difference Based on Probabilistic Histogram." Procedia Computer Science 86 (2016): 265–68. http://dx.doi.org/10.1016/j.procs.2016.05.052.

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Zhu, Nan, Junge Shen, and Xiaotong Niu. "Double JPEG Compression Detection Based on Noise-Free DCT Coefficients Mixture Histogram Model." Symmetry 11, no. 9 (2019): 1119. http://dx.doi.org/10.3390/sym11091119.

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With the wide use of various image altering tools, digital image manipulation becomes very convenient and easy, which makes the detection of image originality and authenticity significant. Among various image tampering detection tools, double JPEG image compression detector, which is not sensitive to specific image tampering operation, has received large attention. In this paper, we propose an improved double JPEG compression detection method based on noise-free DCT (Discrete Cosine Transform) coefficients mixture histogram model. Specifically, we first extract the block-wise DCT coefficients histogram and eliminate the quantization noise which introduced by rounding and truncation operations. Then, for each DCT frequency, a posterior probability can be obtained by solving the DCT coefficients mixture histogram with a simplified model. Finally, the probabilities from all the DCT frequencies are accumulated to give the posterior probability of a DCT block being authentic or tampered. Extensive experimental results in both quantitative and qualitative terms prove the superiority of our proposed method when compared with the state-of-the-art methods.
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Liu, Xiao Lei. "Dance Movement Recognition Based on Multimodal Environmental Monitoring Data." Journal of Environmental and Public Health 2022 (July 19, 2022): 1–8. http://dx.doi.org/10.1155/2022/1568930.

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Fine motion recognition is a challenging topic in computer vision, and it has been a trendy research direction in recent years. This study combines motion recognition technology with dance movements and the problems such as the high complexity of dance movements and fully considers the human body’s self-occlusion. The excellent motion recognition content in the dance field was studied and analyzed. A compelling feature extraction method was proposed for the dance video dataset, segmented video, and accumulated edge feature operation. By extracting directional gradient histogram features, a set of directional gradient histogram feature vectors is used to characterize the shape features of the dance video movements. A dance movement recognition method is adopted based on the fusion direction gradient histogram feature, optical flow direction histogram feature, and audio signature feature. Three components are combined for dance movement recognition by a multicore learning method. Experimental results show that the cumulative edge feature algorithm proposed in this study outperforms traditional models in the recognition results of HOG features extracted from images. After adding edge features, the description of the dance movement shape is more effective. The algorithm can guarantee a specific recognition rate of complex dance movements. The results also verify the effectiveness of the movement recognition algorithm in this study for dance movement recognition.
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Lee, Byunguk, Wonho Kim, and Seunghwan Lee. "An Extended Vector Polar Histogram Method Using Omni-Directional LiDAR Information." Symmetry 15, no. 8 (2023): 1545. http://dx.doi.org/10.3390/sym15081545.

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This study presents an extended vector polar histogram (EVPH) method for efficient robot navigation using omni-directional LiDAR data. Although the conventional vector polar histogram (VPH) method is a powerful technique suitable for LiDAR sensors, it is limited in its sensing range by the single LiDAR sensor to a semicircle. To address this limitation, the EVPH method incorporates multiple LiDAR sensor’s data for omni-directional sensing. First off, in the EVPH method, the LiDAR sensor coordinate systems are directly transformed into the robot coordinate system to obtain an omni-directional polar histogram. Several techniques are also employed in this process, such as minimum value selection and linear interpolation, to generate a uniform omni-directional polar histogram. The resulting histogram is modified to represent the robot as a single point. Subsequently, consecutive points in the histogram are grouped to construct a symbol function for excluding concave blocks and a threshold function for safety. These functions are combined to determine the maximum cost value that generates the robot’s next heading angle. Robot backward motion is made feasible based on the determined heading angle, enabling the calculation of the velocity vector for time-efficient and collision-free navigation. To assess the efficacy of the proposed EVPH method, experiments were carried out in two environments where humans and obstacles coexist. The results showed that, compared to the conventional method, the robot traveled safely and efficiently in terms of the accumulated amount of rotations, total traveling distance, and time using the EVPH method. In the future, our plan includes enhancing the robustness of the proposed method in congested environments by integrating parameter adaptation and dynamic object estimation methods.
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Xu, Kuan-Man. "Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms." Monthly Weather Review 134, no. 5 (2006): 1442–53. http://dx.doi.org/10.1175/mwr3133.1.

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Abstract A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries–Matusita distance, and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called “cloud objects.” Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object, and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.
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Myung, Jinbok, Kwang-Ho Kim, Jeong-sik Park, Myoung-Wan Koo, and Ji-Hwan Kim. "Two-pass search strategy using accumulated band energy histogram for HMM-based identification of perceptually identical music." International Journal of Imaging Systems and Technology 23, no. 2 (2013): 127–32. http://dx.doi.org/10.1002/ima.22043.

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Hadi, Israa, and Mustafa Sabah. "Upgrade Video Tracking Technique Using Enhanced Hybrid Cat Swarm Optimization Based on Multi Target Model and Accumulated Histogram." Journal of Computational and Theoretical Nanoscience 12, no. 11 (2015): 4017–27. http://dx.doi.org/10.1166/jctn.2015.4313.

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Yoon, Rina, Seokjin Oh, Seungmyeong Cho, and Kyeong-Sik Min. "Memristor–CMOS Hybrid Circuits Implementing Event-Driven Neural Networks for Dynamic Vision Sensor Camera." Micromachines 15, no. 4 (2024): 426. http://dx.doi.org/10.3390/mi15040426.

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For processing streaming events from a Dynamic Vision Sensor camera, two types of neural networks can be considered. One are spiking neural networks, where simple spike-based computation is suitable for low-power consumption, but the discontinuity in spikes can make the training complicated in terms of hardware. The other one are digital Complementary Metal Oxide Semiconductor (CMOS)-based neural networks that can be trained directly using the normal backpropagation algorithm. However, the hardware and energy overhead can be significantly large, because all streaming events must be accumulated and converted into histogram data, which requires a large amount of memory such as SRAM. In this paper, to combine the spike-based operation with the normal backpropagation algorithm, memristor–CMOS hybrid circuits are proposed for implementing event-driven neural networks in hardware. The proposed hybrid circuits are composed of input neurons, synaptic crossbars, hidden/output neurons, and a neural network’s controller. Firstly, the input neurons perform preprocessing for the DVS camera’s events. The events are converted to histogram data using very simple memristor-based latches in the input neurons. After preprocessing the events, the converted histogram data are delivered to an ANN implemented using synaptic memristor crossbars. The memristor crossbars can perform low-power Multiply–Accumulate (MAC) calculations according to the memristor’s current–voltage relationship. The hidden and output neurons can convert the crossbar’s column currents to the output voltages according to the Rectified Linear Unit (ReLU) activation function. The neural network’s controller adjusts the MAC calculation frequency according to the workload of the event computation. Moreover, the controller can disable the MAC calculation clock automatically to minimize unnecessary power consumption. The proposed hybrid circuits have been verified by circuit simulation for several event-based datasets such as POKER-DVS and MNIST-DVS. The circuit simulation results indicate that the neural network’s performance proposed in this paper is degraded by as low as 0.5% while saving as much as 79% in power consumption for POKER-DVS. The recognition rate of the proposed scheme is lower by 0.75% compared to the conventional one, for the MNIST-DVS dataset. In spite of this little loss, the power consumption can be reduced by as much as 75% for the proposed scheme.
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Book chapters on the topic "Accumulated histogram"

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Lucena, Manuel, Nicolás Pérez de la Blanca, José Manuel Fuertes, and Manuel Jesús Marín-Jiménez. "Human Action Recognition Using Optical Flow Accumulated Local Histograms." In Pattern Recognition and Image Analysis. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02172-5_6.

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Conference papers on the topic "Accumulated histogram"

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Wu, Xiaomeng, Takahito Kawanishi, and Kunio Kashino. "Reflectance-Guided, Contrast-Accumulated Histogram Equalization." In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9054004.

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Onoguchi, K. "Moving Object Detection Using a Cross Correlation between a Short Accumulated Histogram and a Long Accumulated Histogram." In 18th International Conference on Pattern Recognition (ICPR'06). IEEE, 2006. http://dx.doi.org/10.1109/icpr.2006.819.

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Wu, Xiaomeng, Xinhao Liu, Kaoru Hiramatsu, and Kunio Kashino. "Contrast-accumulated histogram equalization for image enhancement." In 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017. http://dx.doi.org/10.1109/icip.2017.8296871.

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Aye, Hnin Mya, and Sai Maung Maung Zaw. "Histogram of Accumulated Changing Gradient Orientation (HACGO) for saliency navigated action recognition." In 2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD). IEEE, 2017. http://dx.doi.org/10.1109/snpd.2017.8022726.

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Hübel, Hartwig, and Bastian Vollrath. "Simplified Analysis of Strains Accumulated in the State of Elastic Shakedown Considering Multi-Parameter Loadings." In ASME 2018 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/pvp2018-84070.

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In case of cyclic loading, strain may accumulate due to a ratcheting mechanism until the state of shakedown is possibly achieved. Design Codes frequently require strain limits to be satisfied at the end of the specified lifetime of the structure. However, this requirement is sometimes tied to misleading prerequisites, and little guidance is provided on how the strains accumulated in the state of shakedown can be calculated. Incremental elastic-plastic analyses which require to go step-by-step through many cycles of a given load histogram are rather costly in terms of engineering time and numerical effort. As an alternative, the Simplified Theory of Plastic Zones (STPZ) is used in the present paper. Being a direct method, effects from load history are disregarded. The theory is described shortly and exemplarily applied to a simplification of a pipe bend and a straight pipe, both subjected to combinations of several loads which vary independently from each other so that a multidimensional load domain is represented. It is shown that the Simplified Theory of Plastic Zones is well suited to provide reasonable estimates of strains accumulated in the state of elastic shakedown at the cost of few linear elastic analyses.
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Samaria, Sagar, Bob Zhang, Sudhakar Tallavajhula, and Johyun Kyoung. "Structural Connection Fatigue Evaluation Methodology Using Time Domain Approach." In ASME 2020 39th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/omae2020-18229.

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Abstract There is an ever-increasing demand for life extension of existing floating platforms worldwide. To adequately support these life extension projects there is a need to predict fatigue life of floating structures more accurately using a time domain approach. However, structural fatigue damage calculations using time domain response analysis can be very time consuming and challenging. An efficient and effective structural analysis methodology is developed to calculate accumulated fatigue damage for structural connections in a floating offshore platform using a response-based time domain routine. The methodology discussed in this paper can be applied to estimate fatigue life for hull critical connections in floaters such as Spars, TLPs or Semis as well as local structural supports such as mooring foundations and riser foundations. It also provides the option to generate stress histograms that can be utilized for Fracture Mechanics Evaluation (FME) of welds in structural connections. To calculate the accumulated fatigue damage at desired locations on a floating platform, the time domain analysis employs a Stress Intensification Factor (SIF) which correlates global loads with local stresses. In cases where a crack initiation is observed on a structural connection, fracture mechanics is used to evaluate the structural integrity of the weld. The FME requires fatigue stress range histograms as one of the input parameters. The stress ranges and cycles that are calculated and used to compute the fatigue damage using this methodology can be converted to stress range histograms which can then be used in the FME. The standard method to compute fatigue damage for a structural connection is by using an S-N fatigue approach under the assumption of linear cumulative damage (Palmgren-Miner rule). The methodology discussed in this paper uses a rainflow counting algorithm to effectively calculate the stress range and cycles which are then utilized for computing the fatigue damage. This methodology can be applied to green field projects involving a new design or for life of field studies of an existing platform requiring life extensions. It is particularly beneficial for brownfield projects where more accurate re-evaluation of fatigue life is needed. It can also provide Clients with reliable Engineering Criticality Assessments (ECA) and enable them to plan in-service inspections and repair work. As an application, a typical truss connection for a Spar platform is used to evaluate structural fatigue damage and generate the stress range histogram for FME. Also, a comparative study is performed for a typical truss connection fatigue damage result between the traditional approach used and the method discussed in this paper.
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O’Connor, Sean, Junhee Kim, Jerome P. Lynch, Kincho H. Law, and Liming Salvino. "Fatigue Life Monitoring of Metallic Structures by Decentralized Rainflow Counting Embedded in a Wireless Sensor Network." In ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2010. http://dx.doi.org/10.1115/smasis2010-3839.

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Fatigue is one of the most widespread damage mechanisms found in metallic structures. Fatigue is an accumulated degradation process that occurs under cyclic loading, eventually inducing cracking at stress concentration points. Fatigue-related cracking in operating structures is closely related with statistical loading characteristics, such as the number of load cycles, cycle amplitudes and means. With fatigue cracking a prevalent failure mechanism of many engineered structures including ships, bridges and machines, among others, a reliable method of fatigue life estimation is direly needed for future structural health monitoring systems. In this study, a strategy for fatigue life estimation by a wireless sensor network installed in a structure for autonomous health monitoring is proposed. Specifically, the computational resources available at the sensor node are leveraged to compress raw strain time histories of a structure into a more meaningful and compressed form. Simultaneous strain sensing and on-board rainflow counting are conducted at individual wireless sensors with fatigue life prediction made using extracted amplitudes and means. These parameters are continuously updated during long-term monitoring of the structure. Histograms of strain amplitudes and means stored in the wireless sensor represent a highly compressed form of the original raw data. Communication of the histogram only needs to be done by request, dramatically reducing power consumption in the wireless sensing network. Experimental tests with aluminum specimens in the laboratory are executed for verification of the proposed damage detection strategy.
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McLauchlan, Philip, and John Mayhew. "Needles: A Stereo Algorithm for Texture." In Image Understanding and Machine Vision. Optica Publishing Group, 1989. http://dx.doi.org/10.1364/iumv.1989.tud1.

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This paper describes Needles, an edge based stereo algorithm designed to take advantage of the smoothness of many textured surfaces. The correspondence problem is not addressed explicitly. Rather, a simple two stage process extracts surface position and orientation directly. Firstly local disparity histograms over a large range are constructed. Maxima in the histograms correspond to the possible surface depths. A Hough transform is used to fit a plane to the ambiguous disparity points close to the histogram maxima. This confirms and makes more precise the estimates of disparity obtained from the histograms. Local surface disparity and orientation are calculated from the best planar fit after all the histogram maxima (above a threshold) have been tried. This is an extension of an algorithm described in (Pollard 1985) which uses a Hough transform to find local surface orientation without explicit matching. In his algorithm pairs of possible matches vote for the disparity gradient between them. When all pairs have voted the winning disparity gradient (and hence, surface orientation) has the highest Hough accumulator value.
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Xiaojie Li, Weilan Wang, and Wei Yang. "Improved local accumulate histogram-based Thangka Image Retrieval." In 2010 International Conference on Image Analysis and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/iasp.2010.5476104.

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Gu, Honglu, Haiyan Guo, Fanshun Meng, Xiaomin Li, and Fuheng Li. "Study on the Collision Probability of Tandem Top-Tensioned Risers Based on the Extremes Statistical Methodology." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-132224.

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Abstract This paper aims to develop an integrated model for predicting the probability of riser collisions. This model can fully utilize the limited time series samples and dramatically reduce the computational time consumption required to accumulate enough data samples. First, a global mechanical model for the dual-riser system, which considers the current, random wave, top motion, and hydrodynamic interference effects, is constructed based on the vector form intrinsic finite element. Then, an analytical geometry-based procedure is coded, and a three-stage sieving strategy is proposed to efficiently obtain a random time series sample of the minimum distance, Cmin (t). The distribution parameters of this sample for various extreme value distributions are determined by the maximum likelihood estimation. The χ2 test, histograms, and quantile plots are used together to further assess the fitting quality of each theoretical model to the sample, and determine the optimal probability distribution form. Based on this optimal extreme value distribution model, the crossing rate of the sample is extrapolated to the failure threshold to predict the collision probability. Moreover, the probability prediction results are verified by Monte Carlo simulation and compared with the Gumbel probability paper method.
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