Relevant bibliographies by topics / FUZZY THRESHOLDING AND ANR

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'FUZZY THRESHOLDING AND ANR'

Author: Grafiati
Published: 11 September 2023
Last updated: 31 July 2025

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Journal articles on the topic "FUZZY THRESHOLDING AND ANR"

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Nobuhara, Hajime, and Kaoru Hirota. "A Fuzzification of Morphological Wavelets Based on Fuzzy Relational Calculus and its Application to Image Compression/Reconstruction." Journal of Advanced Computational Intelligence and Intelligent Informatics 8, no. 4 (2004): 373–78. http://dx.doi.org/10.20965/jaciii.2004.p0373.

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A new style of fuzzy wavelets is proposed by the fuzzification of morphological wavelets. Due to the correspondence of the morphological wavelets operations and fuzzy relational ones, wavelets analysis/synthesis schemes can be formulated based on fuzzy relational calculus. To enable efficient image compression/reconstruction, the concept of the alpha-band which is an alpha-cut generalization, is also proposed for thresholding wavelets. In an image compression/reconstruction experiment using test images extracted from the Standard Image DataBAse (SIDBA), it is confirmed that the root mean squar
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Pal, Sankar K., and Ambarish Dasgupta. "Spectral fuzzy sets and soft thresholding." Information Sciences 65, no. 1-2 (1992): 65–97. http://dx.doi.org/10.1016/0020-0255(92)90078-m.

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Bhandari, Dinabandhu, Nikhil R. Pal, and D. Dutta Majumder. "Fuzzy divergence, probability measure of fuzzy events and image thresholding." Pattern Recognition Letters 13, no. 12 (1992): 857–67. http://dx.doi.org/10.1016/0167-8655(92)90085-e.

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Sowjanya, Kotte, Munazzar Ajreen, Paka Sidharth, Kakara Sriharsha, and Lade Aishwarya Rao. "Fuzzy thresholding technique for multiregion picture division." International Research Journal on Advanced Science Hub 4, no. 03 (2022): 45–50. http://dx.doi.org/10.47392/irjash.2022.011.

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Tizhoosh, Hamid R. "Image thresholding using type II fuzzy sets." Pattern Recognition 38, no. 12 (2005): 2363–72. http://dx.doi.org/10.1016/j.patcog.2005.02.014.

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CHENG, H. D., YANHUI GUO, and YINGTAO ZHANG. "A NOVEL APPROACH TO IMAGE THRESHOLDING BASED ON 2D HOMOGENEITY HISTOGRAM AND MAXIMUM FUZZY ENTROPY." New Mathematics and Natural Computation 07, no. 01 (2011): 105–33. http://dx.doi.org/10.1142/s1793005711001834.

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Image thresholding is an important topic for image processing, pattern recognition and computer vision. Fuzzy set theory has been successfully applied to many areas, and it is generally believed that image processing bears some fuzziness in nature. In this paper, we employ the newly proposed 2D homogeneity histogram (homogram) and the maximum fuzzy entropy principle to perform thresholding. We have conducted experiments on a variety of images. The experimental results demonstrate that the proposed approach can select the thresholds automatically and effectively. Especially, it not only can pro
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Bogiatzis, Athanasios, and Basil Papadopoulos. "Global Image Thresholding Adaptive Neuro-Fuzzy Inference System Trained with Fuzzy Inclusion and Entropy Measures." Symmetry 11, no. 2 (2019): 286. http://dx.doi.org/10.3390/sym11020286.

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Thresholding algorithms segment an image into two parts (foreground and background) by producing a binary version of our initial input. It is a complex procedure (due to the distinctive characteristics of each image) which often constitutes the initial step of other image processing or computer vision applications. Global techniques calculate a single threshold for the whole image while local techniques calculate a different threshold for each pixel based on specific attributes of its local area. In some of our previous work, we introduced some specific fuzzy inclusion and entropy measures whi
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Shark, L. K., and C. Yu. "Denoising by optimal fuzzy thresholding in wavelet domain." Electronics Letters 36, no. 6 (2000): 581. http://dx.doi.org/10.1049/el:20000451.

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Li, Linguo, Xuwen Huang, Shunqiang Qian, Zhangfei Li, Shujing Li, and Romany F. Mansour. "Fuzzy Hybrid Coyote Optimization Algorithm for Image Thresholding." Computers, Materials & Continua 72, no. 2 (2022): 3073–90. http://dx.doi.org/10.32604/cmc.2022.026625.

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Barrenechea, E., H. Bustince, M. J. Campión, E. Induráin, and V. Knoblauch. "Topological interpretations of fuzzy subsets. A unified approach for fuzzy thresholding algorithms." Knowledge-Based Systems 54 (December 2013): 163–71. http://dx.doi.org/10.1016/j.knosys.2013.09.008.

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Dissertations / Theses on the topic "FUZZY THRESHOLDING AND ANR"

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Zhao, Mansuo. "Image Thresholding Technique Based On Fuzzy Partition And Entropy Maximization." University of Sydney. School of Electrical and Information Engineering, 2005. http://hdl.handle.net/2123/699.

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Thresholding is a commonly used technique in image segmentation because of its fast and easy application. For this reason threshold selection is an important issue. There are two general approaches to threshold selection. One approach is based on the histogram of the image while the other is based on the gray scale information located in the local small areas. The histogram of an image contains some statistical data of the grayscale or color ingredients. In this thesis, an adaptive logical thresholding method is proposed for the binarization of blueprint images first. The new method exploits t
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Zhao, Mansuo. "Image Thresholding Technique Based On Fuzzy Partition And Entropy Maximization." Thesis, The University of Sydney, 2004. http://hdl.handle.net/2123/699.

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Thresholding is a commonly used technique in image segmentation because of its fast and easy application. For this reason threshold selection is an important issue. There are two general approaches to threshold selection. One approach is based on the histogram of the image while the other is based on the gray scale information located in the local small areas. The histogram of an image contains some statistical data of the grayscale or color ingredients. In this thesis, an adaptive logical thresholding method is proposed for the binarization of blueprint images first. The new method exploits t
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Almotiri, Jasem. "A Multi-Anatomical Retinal Structure Segmentation System for Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding." Thesis, University of Bridgeport, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10975223.

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<p> Eye exam can be as efficacious as physical one in determining health concerns. Retina screening can be the very first clue to detecting a variety of hidden health issues including pre-diabetes and diabetes. Through the process of clinical diagnosis and prognosis; ophthalmologists rely heavily on the binary segmented version of retina fundus image; where the accuracy of segmented vessels, optic disc and abnormal lesions extremely affects the diagnosis accuracy which in turn affect the subsequent clinical treatment steps. This thesis proposes an automated retinal fundus image segmentation sy
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Al-Azawi, Mohammad Ali Naji Said. "A new approach to automatic saliency identification in images based on irregularity of regions." Thesis, De Montfort University, 2015. http://hdl.handle.net/2086/11122.

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This research introduces an image retrieval system which is, in different ways, inspired by the human vision system. The main problems with existing machine vision systems and image understanding are studied and identified, in order to design a system that relies on human image understanding. The main improvement of the developed system is that it uses the human attention principles in the process of image contents identification. Human attention shall be represented by saliency extraction algorithms, which extract the salient regions or in other words, the regions of interest. This work prese
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Čambalová, Kateřina. "Volné algebraické struktury a jejich využití pro segmentaci digitálního obrazu." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-231711.

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The thesis covers methods for image segmentation. Fuzzy segmentation is based on the thresholding method. This is generalized to accept multiple criteria. The whole process is mathematically based on the free algebra theory. Free distributive lattice is created from poset of elements based on image properties and the lattice members are represented by terms used by the threshoding. Possible segmentation results compose the equivalence classes distribution. The thesis also contains description of resulting algorithms and methods for their optimization. Also the method of area subtracting is int
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SNEKHA. "GENETIC ALGORITHM BASED ECG SIGNAL DE-NOISING USING EEMD AND FUZZY THRESHOLDING." Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15346.

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ElectroCardioGram (ECG) signal records electrical conduction activity of heart. These are very small signals in strength with narrow bandwidth of 0.05-120 Hz. Physicians especially cardiologist use these signals for diagnosis of the heart’s condition or heart diseases. ECG signal is contaminated with various artifacts such as Power Line Interference (PLI), Patient–electrode motion artifacts, Electrode-pop or contact noise, and Baseline Wandering and ElectroMyoGraphic (EMG) noise during acquisition. Analysis of ECG signals becomes difficult to inspect the cardiac activity in the presence
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Tanjung, Guntur. "A study on image change detection methods for multiple images of the same scene acquired by a mobile camera." Thesis, 2010. http://hdl.handle.net/2440/60533.

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Detecting regions of change while reducing unimportant changes in multiple outdoor images of the same scene containing fence wires (i.e., a chain-link mesh fence) acquired by a mobile camera from slightly different viewing positions, angles and at different times is a very difficult problem. Regions of change include appearing of new objects and/or disappearing of old objects behind fence wires, breaches in the integrity of fence wires and attached objects in front of fence wires. Unimportant changes are mainly caused by camera movement, considerable background clutter, illumination variation,
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Tanjung, Guntur. "A study on image change detection methods for multiple images of the same scene acquired by a mobile camera." 2010. http://hdl.handle.net/2440/60533.

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Detecting regions of change while reducing unimportant changes in multiple outdoor images of the same scene containing fence wires (i.e., a chain-link mesh fence) acquired by a mobile camera from slightly different viewing positions, angles and at different times is a very difficult problem. Regions of change include appearing of new objects and/or disappearing of old objects behind fence wires, breaches in the integrity of fence wires and attached objects in front of fence wires. Unimportant changes are mainly caused by camera movement, considerable background clutter, illumination variation,
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Ensafi, Pegah. "Weighted Opposition-Based Fuzzy Thresholding." Thesis, 2011. http://hdl.handle.net/10012/5796.

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With the rapid growth of the digital imaging, image processing techniques are widely involved in many industrial and medical applications. Image thresholding plays an essential role in image processing and computer vision applications. It has a vast domain of usage. Areas such document image analysis, scene or map processing, satellite imaging and material inspection in quality control tasks are examples of applications that employ image thresholding or segmentation to extract useful information from images. Medical image processing is another area that has extensively used image threshold
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Bai, Rong. "Wavelet Shrinkage Based Image Denoising using Soft Computing." Thesis, 2008. http://hdl.handle.net/10012/3876.

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Noise reduction is an open problem and has received considerable attention in the literature for several decades. Over the last two decades, wavelet based methods have been applied to the problem of noise reduction and have been shown to outperform the traditional Wiener filter, Median filter, and modified Lee filter in terms of root mean squared error (MSE), peak signal noise ratio (PSNR) and other evaluation methods. In this research, two approaches for the development of high performance algorithms for de-noising are proposed, both based on soft computing tools, such as fuzzy logic, ne
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Book chapters on the topic "FUZZY THRESHOLDING AND ANR"

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Forero-Vargas, Manuel Guillermo. "Fuzzy Thresholding and Histogram Analysis." In Fuzzy Filters for Image Processing. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-36420-7_6.

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Oh, Jun-Taek, and Wook-Hyun Kim. "EWFCM Algorithm and Region-Based Multi-level Thresholding." In Fuzzy Systems and Knowledge Discovery. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11881599_107.

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Li, Jianli, Bingbin Dai, Kai Xiao, and Aboul Ella Hassanien. "Density Based Fuzzy Thresholding for Image Segmentation." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35326-0_13.

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Roy, Sudipta, Nidul Sinha, and Asoke Kr Sen. "Fuzzy Soft Thresholding Based Hybrid Denoising Model." In Advances in Digital Image Processing and Information Technology. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24055-3_1.

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Kubicek, Jan, Marek Penhaker, Iveta Bryjova, and Martin Augustynek. "Classification Method for Macular Lesions Using Fuzzy Thresholding Method." In XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32703-7_48.

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Bruzzese, D., and U. Giani. "Automatic Multilevel Thresholding Based on a Fuzzy Entropy Measure." In Classification and Multivariate Analysis for Complex Data Structures. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13312-1_12.

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Vlachos, Ioannis K., and George D. Sergiadis. "An Automated Image Thresholding Scheme for Highly Contrast-Degraded Images Based on a-Order Fuzzy Entropy." In Fuzzy Logic and Applications. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/10983652_40.

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Moreno, Ginés, Jaime Penabad, José A. Riaza, and Germán Vidal. "Symbolic Execution and Thresholding for Efficiently Tuning Fuzzy Logic Programs." In Logic-Based Program Synthesis and Transformation. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63139-4_8.

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Shah, Vrishani, and Anand J. Kulkarni. "Steganography Based on Fuzzy Edge Detection, Cohort Intelligence, and Thresholding." In Handbook of Formal Optimization. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3820-5_55.

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Shah, Vrishani, and Anand J. Kulkarni. "Steganography Based on Fuzzy Edge Detection, Cohort Intelligence and Thresholding." In Handbook of Formal Optimization. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-19-8851-6_55-1.

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Conference papers on the topic "FUZZY THRESHOLDING AND ANR"

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Reddy, CH Venkateswara, K. Vidhya, and EMG Subramanian. "Expression of Concern for: Evaluation of Cup to Disc Ratio for Glaucoma detection through optic cup and disc segmentation using Fuzzy C-means clustering and comparing with adaptive thresholding method." In 2022 14th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS). IEEE, 2022. http://dx.doi.org/10.1109/macs56771.2022.10703547.

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Wu, Weishu, Changxi Yang, Scott Campbell, and Pochi Yeh. "A Photorefractive Optical Fuzzy Logic Processor." In Optical Computing. Optica Publishing Group, 1995. http://dx.doi.org/10.1364/optcomp.1995.otue10.

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Fuzzy logic 1 has potential application in fields such as pattern recognition and process control. Since Liu first introduced an optical fuzzy logic processor utilizing a lens-array-based multiple imaging system, 2 many other systems have also been proposed and demonstrated. Most of early implementations were based on the principle of shadow-casting, with spatially encoded patterns being superimposed on each other by use of either light source array 3 or lens-array. 2 To obtain correct output of the fuzzy logic maximization (or minimization) operations, thresholding devices were needed in some
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Thakkar, Mehul, and Hitesh Shah. "Edge detection techniques using fuzzy thresholding." In 2011 World Congress on Information and Communication Technologies (WICT). IEEE, 2011. http://dx.doi.org/10.1109/wict.2011.6141263.

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Ichihashi, Hidetomo, Toshiro Ogita, Katsuhiro Honda, and Akira Notsu. "Improvement by sorting and thresholding in PCA based nearest neighbor search." In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2012. http://dx.doi.org/10.1109/fuzz-ieee.2012.6250773.

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Othman, A., H. R. Tizhoosh, and F. Khalvati. "Self-Configuring and Evolving Fuzzy Image Thresholding." In 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA). IEEE, 2015. http://dx.doi.org/10.1109/icmla.2015.130.

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Dash, Ajaya Kumar, and Banshidhar Majhi. "Image segmentation using fuzzy based histogram thresholding." In 2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES). IEEE, 2015. http://dx.doi.org/10.1109/spices.2015.7091443.

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Rajesh, R., N. Senthilkumaran, J. Satheeshkumar, B. Shanmuga Priya, C. Thilagavathy, and K. Priya. "On the type-1 and type-2 fuzziness measures for thresholding MRI brain images." In 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2011. http://dx.doi.org/10.1109/fuzzy.2011.6007444.

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Cheng, Heng-Da, and Yen-Hung Chen. "Novel fuzzy entropy approach to thresholding and enhancement." In Medical Imaging '98, edited by Kenneth M. Hanson. SPIE, 1998. http://dx.doi.org/10.1117/12.310977.

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Thakkar, Mehul, and Hitesh Shah. "Automatic thresholding in edge detection using fuzzy approach." In 2010 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). IEEE, 2010. http://dx.doi.org/10.1109/iccic.2010.5705868.

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Amaral, T. G., M. M. Crisostomo, and A. Traca de Almeida. "Image thresholding by minimisation of fuzzy compactness and linear index of fuzziness." In Proceedings of 8th International Fuzzy Systems Conference. IEEE, 1999. http://dx.doi.org/10.1109/fuzzy.1999.793111.

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