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Relevant bibliographies by topics / Histogram pattern analysis

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Academic literature on the topic 'Histogram pattern analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Histogram pattern analysis"

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Van Zyl-Bulitta, Verena Helen, R. Otte, and JH Van Rooyen. "Layer histogram patterns in financial time series." Corporate Ownership and Control 6, no. 3 (2009): 137–46. http://dx.doi.org/10.22495/cocv6i3p13.

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This study aims to investigate whether the phenomena found by Shnoll et al. when applying histogram pattern analysis techniques to stochastic processes from chemistry and physics are also present in financial time series, particularly exchange rate and index data. The phenomena are related to fine structure of non-smoothed frequency distributions drawn from statistically insufficient samples of changes and their patterns in time. Shnoll et al. use the notion of macroscopic fluctuations (MF) to explain the behavior of sequences of histograms. Histogram patterns in time adhere to several laws th

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Van Rooyen, JH. "Searching for histogram patterns in USD/ZAR foreign exchange financial time series." Corporate Ownership and Control 6, no. 4 (2009): 575–84. http://dx.doi.org/10.22495/cocv6i4sip9.

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This study aims to investigate whether the phenomena found by Shnoll et al. when applying histogram pattern analysis techniques to stochastic processes from chemistry and physics are also present in financial time series, particularly exchange rate data. The phenomena are related to fine structure of non-smoothed frequency distributions drawn from tick high frequency currency exchange rates over a period of one week. Shnoll et al. use the notion of macroscopic fluctuations (MF) to explain the behaviour of sequences of histograms. Histogram patterns in time adhere to several laws that could not

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Ning, Jinfeng, Vaughn G. Braxton, Ying Wang, Michael A. Sutton, Yanqing Wang, and Susan M. Lessner. "Speckle Patterning of Soft Tissues for Strain Field Measurement Using Digital Image Correlation: Preliminary Quality Assessment of Patterns." Microscopy and Microanalysis 17, no. 1 (2010): 81–90. http://dx.doi.org/10.1017/s1431927610094377.

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AbstractMethods for creating speckle patterns on mouse arteries for use in deformation and strain field measurements in a stereomicroscope digital image correlation (DIC) system are described. Both fluorescent microsphere binding and ethidium bromide (EB) nuclear staining were used to generate high contrast, random patterns on mouse carotid arteries. To quantify the quality of each pattern, several metrics are used including (a) histogram distribution for each intensity pattern and (b) pixel-level variance in intensity pattern noise. Results demonstrate that both approaches provide sufficient

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Ahmadi, Shiva, Ahmad Mani-Varnosfaderani, and Biuck Habibi. "Motor Oil Classification Using Color Histograms and Pattern Recognition Techniques." Journal of AOAC INTERNATIONAL 101, no. 6 (2018): 1967–76. http://dx.doi.org/10.5740/jaoacint.17-0308.

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Abstract Motor oil classification is important for quality control and the identification of oil adulteration. In this work, we propose a simple, rapid, inexpensive and nondestructive approach based on image analysis and pattern recognition techniques for the classification of nine different types of motor oils according to their corresponding color histograms. For this, we applied color histogram in different color spaces such as red green blue (RGB), grayscale, and hue saturation intensity (HSI) in order to extract features that can help with the classification procedure. These color histogr

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Li, Ya-Feng, Ren-Er Yang, Jie Cheng, and Hong-Zhu Dai. "A Steganography Embedding Method Based on Hamming Coding and Histogram-Preserving." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 14 (2019): 1954039. http://dx.doi.org/10.1142/s0218001419540399.

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This paper proposes an information hiding algorithm using matrix embedding with Hamming codes and histogram preservation in order to keep the histogram of the image unchanged before and after hiding information in digital media. First, the algorithm uses matrix embedding with Hamming codes to determine the rewriting bits of the original image, rewrite and flip them, and successfully embed the secret information. Then, according to the idea of a break-even point, a balanced pixel frequency adaptive algorithm is proposed and each embedded bit of secret information is detected and compensated by

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Carlotto, Mark J. "Histogram Analysis Using a Scale-Space Approach." IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-9, no. 1 (1987): 121–29. http://dx.doi.org/10.1109/tpami.1987.4767877.

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Iliev, P., and L. Tsekov. "Motion detection using image histogram sequence analysis." Signal Processing 30, no. 3 (1993): 373–84. http://dx.doi.org/10.1016/0165-1684(93)90018-6.

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Payabvash, Seyedmehdi, Tarik Tihan, and Soonmee Cha. "Volumetric voxelwise apparent diffusion coefficient histogram analysis for differentiation of the fourth ventricular tumors." Neuroradiology Journal 31, no. 6 (2018): 554–64. http://dx.doi.org/10.1177/1971400918800803.

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Purpose We applied voxelwise apparent diffusion coefficient (ADC) histogram analysis in addition to structural magnetic resonance imaging (MRI) findings and patients’ age for differentiation of intraaxial posterior fossa tumors involving the fourth ventricle. Participants and methods Pretreatment MRIs of 74 patients with intraaxial brain neoplasm involving the fourth ventricle, from January 1, 2004 to December 31, 2015, were reviewed. The tumor solid components were segmented and voxelwise ADC histogram variables were determined. Histogram-driven variables, structural MRI findings, and patient

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Hardalaç, Naciye. "A computational analysis on similarities and dissimilarities of Acem Kurdi, Kurdi and Muhayyer Kurdi makams in Turkish music." African Educational Research Journal 8, no. 4 (2020): 761–73. http://dx.doi.org/10.30918/aerj.84.20.158.

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In Turkish music, it is possible to find different makams sharing the same core scale of notes. The subjects of this study are three such makams, namely Acem Küdri, Kürdi, Muhayyer Kürdi. We use computational analysis based on histograms, pattern search and dynamic time warping to reveal the similarities and dissimilarities of these three makams. On the one hand, our results show that a time independent histogram analysis is unable to properly highlight the differences between different makams. On the other hand, our study also reveals that a time dependent analysis is well suited for the iden

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Kriston-Vizi, Janos, Ching Aeng Lim, Peter Condron, Kelvin Chua, Martin Wasser, and Horst Flotow. "An Automated High-Content Screening Image Analysis Pipeline for the Identification of Selective Autophagic Inducers in Human Cancer Cell Lines." Journal of Biomolecular Screening 15, no. 7 (2010): 869–81. http://dx.doi.org/10.1177/1087057110373393.

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Automated image processing is a critical and often rate-limiting step in high-content screening (HCS) workflows. The authors describe an open-source imaging-statistical framework with emphasis on segmentation to identify novel selective pharmacological inducers of autophagy. They screened a human alveolar cancer cell line and evaluated images by both local adaptive and global segmentation. At an individual cell level, region-growing segmentation was compared with histogram-derived segmentation. The histogram approach allowed segmentation of a sporadic-pattern foreground and hence the attainmen

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Dissertations / Theses on the topic "Histogram pattern analysis"

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Van, Zyl Verena Helen. "Searching for histogram patterns due to macroscopic fluctuations in financial time series." Thesis, Stellenbosch : University of Stellenbosch, 2007. http://hdl.handle.net/10019.1/3078.

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Thesis (MComm (Business Management))--University of Stellenbosch, 2007.<br>ENGLISH ABSTRACT: his study aims to investigate whether the phenomena found by Shnoll et al. when applying histogram pattern analysis techniques to stochastic processes from chemistry and physics are also present in financial time series, particularly exchange rate and index data. The phenomena are related to fine structure of non-smoothed frequency distributions drawn from statistically insufficient samples of changes and their patterns in time. Shnoll et al. use the notion of macroscopic fluctuations to explain t

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Zahradnik, Roman. "Texturní příznaky." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2007. http://www.nusl.cz/ntk/nusl-236898.

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Aim of this project is to evaluate effectivity of various texture features within the context of image processing, particulary the task of texture recognition and classification. My work focuses on comparing and discussion of usage and efficiency of texture features based on local binary patterns and co- ccurence matrices. As classification algorithm is concerned, cluster analysis was choosen.

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Chou, Sheng-Che, and 周聖哲. "Analysis and Comparison of Instrumental Music using Spectrum Histogram, Periodicity Histogram and Fluctuation Pattern." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/68032956454611928546.

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碩士<br>國立臺灣大學<br>電信工程學研究所<br>96<br>In this thesis, I introduce three different methods for music similarity measuring in detail. And then I apply these three methods to 50 songs I chose (frankly viewed as 5 groups, each one has 10 songs). By comparing these results, we can understand which method is the most effective and most accurate. Because we can view an audio data in many different views of point, we have to choose a property on which we focus before starting the similarity measures. In this thesis, I choose the property “timbre” as my yardstick. In chapter 2, I describe the property

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Book chapters on the topic "Histogram pattern analysis"

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Delon, Julie, Agnes Desolneux, Jose Luis Lisani, and Ana Belen Petro. "Color Image Segmentation Using Acceptable Histogram Segmentation." In Pattern Recognition and Image Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11492542_30.

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Haijing, Peihua Li, and Tianwen Zhang. "Proposal of Novel Histogram Features for Face Detection." In Pattern Recognition and Image Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11552499_38.

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Antunes, Michel, and João P. Barreto. "Efficient Stereo Matching Using Histogram Aggregation with Multiple Slant Hypotheses." In Pattern Recognition and Image Analysis. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38628-2_1.

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Ramella, Giuliana, and Gabriella Sanniti di Baja. "Multiresolution Histogram Analysis for Color Reduction." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16687-7_8.

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Wattanapanich, Chirawat, Hong Wei, and Wei Xu. "Analysis of Histogram of Oriented Gradients on Gait Recognition." In Pattern Recognition and Artificial Intelligence. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71804-6_7.

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Ahonen, Timo, Jiří Matas, Chu He, and Matti Pietikäinen. "Rotation Invariant Image Description with Local Binary Pattern Histogram Fourier Features." In Image Analysis. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02230-2_7.

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Forero, Manuel G., Carlos Arias-Rubio, and Brigete Tatiana González. "Analytical Comparison of Histogram Distance Measures." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-13469-3_10.

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Cataño, Miguel Angel, and Joan Climent. "A New Morphological Measure of Histogram Bimodality." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33275-3_48.

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Alkalai, Mohamed, and Volker Sorge. "A Histogram-Based Approach to Mathematical Line Segmentation." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41822-8_56.

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Curetti, María, Santiago Garcia Bravo, Gabriela Soledad Arri, and Ladislao Mathé. "Fast Tracking Algorithm with Borders 1-D Histogram Correlation." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33275-3_76.

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Conference papers on the topic "Histogram pattern analysis"

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Li, Wei, Jiu-Hong Ruan, and Hua-An Zhao. "Crowd movement segmentation using velocity field histogram curve." In 2012 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2012. http://dx.doi.org/10.1109/icwapr.2012.6294777.

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McCloskey, Scott, Can Chen, and Jingyi Yu. "Focus Manipulation Detection via Photometric Histogram Analysis." In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2018. http://dx.doi.org/10.1109/cvpr.2018.00180.

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Wang, Mingxiang, Yu L. Mo, and Junli Ma. "Applied method of license plate binarization based on histogram analysis." In Multispectral Image Processing and Pattern Recognition, edited by Bir Bhanu, Jun Shen, and Tianxu Zhang. SPIE, 2001. http://dx.doi.org/10.1117/12.441513.

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Wang, Peng, and Youguang Zhang. "Fingerprint image segmentation based on multi-features histogram analysis." In International Symposium on Multispectral Image Processing and Pattern Recognition, edited by Tianxu Zhang, Carl A. Nardell, Duane D. Smith, and Hangqing Lu. SPIE, 2007. http://dx.doi.org/10.1117/12.750687.

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Newtson, Kathy, and Charles Creusere. "Histogram Oriented Gradients and Map Seeking Circuits pattern recognition with compressed imagery." In 2016 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI). IEEE, 2016. http://dx.doi.org/10.1109/ssiai.2016.7459188.

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Biglari, M., F. Mirzaei, and H. Ebrahimpour-Komeh. "Illumination invariant face recognition using SQI and weighted LBP histogram." In 2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA). IEEE, 2013. http://dx.doi.org/10.1109/pria.2013.6528433.

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Esmaeili, Vida, Mahmood Mohassel Feghhi, and Seyed Omid Shahdi. "Micro-Expression Recognition Using Histogram of Image Gradient Orientation on Diagonal Planes." In 2021 5th International Conference on Pattern Recognition and Image Analysis (IPRIA). IEEE, 2021. http://dx.doi.org/10.1109/ipria53572.2021.9483500.

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Fei-Fei Lee, Koji Kotani, Qiu Chen, and Tadahiro Ohmi. "An improved fast face recognition algorithm based on adjacent pixel intensity difference quantization histogram." In 2008 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR). IEEE, 2008. http://dx.doi.org/10.1109/icwapr.2008.4635796.

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Iraei, Iman, and Karim Faez. "Object tracking with occlusion handling using mean shift, Kalman filter and Edge Histogram." In 2015 2nd International Conference on Pattern Recognition and Image Analysis (IPRIA). IEEE, 2015. http://dx.doi.org/10.1109/pria.2015.7161637.

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Zohrevand, Abbas, Javad Sadri, Zahra Imani, and Mohammad Reza Yeganezad. "Line Segmentation in Persian Handwritten Documents Based on a Novel Projection Histogram Method." In 2019 4th International Conference on Pattern Recognition and Image Analysis (IPRIA). IEEE, 2019. http://dx.doi.org/10.1109/pria.2019.8786006.

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