Texture and Colour in Image Analysis
Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews.
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Format: | Electronic Book Chapter |
Language: | English |
Published: |
Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2021
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Subjects: | |
Online Access: | DOAB: download the publication DOAB: description of the publication |
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041 | 0 | |a eng | |
042 | |a dc | ||
072 | 7 | |a KNTX |2 bicssc | |
100 | 1 | |a Bianconi, Francesco |4 edt | |
700 | 1 | |a Fernández, Antonio |4 edt | |
700 | 1 | |a Sánchez-Yáñez, Raúl E. |4 edt | |
700 | 1 | |a Bianconi, Francesco |4 oth | |
700 | 1 | |a Fernández, Antonio |4 oth | |
700 | 1 | |a Sánchez-Yáñez, Raúl E. |4 oth | |
245 | 1 | 0 | |a Texture and Colour in Image Analysis |
260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2021 | ||
300 | |a 1 electronic resource (278 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Information technology industries |2 bicssc | |
653 | |a Machine vision | ||
653 | |a image analysis | ||
653 | |a item counting device | ||
653 | |a electro-deposition industry | ||
653 | |a digital intraoral radiography | ||
653 | |a image preprocessing | ||
653 | |a periapical lesions | ||
653 | |a texture analysis | ||
653 | |a prostate cancer | ||
653 | |a histopathology | ||
653 | |a microscopic | ||
653 | |a tissue image | ||
653 | |a segmentation | ||
653 | |a morphological | ||
653 | |a quantitative | ||
653 | |a classification | ||
653 | |a SVM | ||
653 | |a image resizing | ||
653 | |a local Tchebichef moments (LTM) | ||
653 | |a scaling | ||
653 | |a scale-and-stretch | ||
653 | |a seam carving | ||
653 | |a faster R-CNN | ||
653 | |a cutting pieces | ||
653 | |a multi-period pattern | ||
653 | |a skew angle | ||
653 | |a period length | ||
653 | |a colored texture pattern classification | ||
653 | |a global-local texture classification | ||
653 | |a color-texture features | ||
653 | |a color-texture feature extraction | ||
653 | |a bagging post-processing | ||
653 | |a BQMP and Haralick global-local feature integration | ||
653 | |a maceral components | ||
653 | |a image segmentation | ||
653 | |a coal petrography | ||
653 | |a random forest | ||
653 | |a two-level clustering | ||
653 | |a deep neural networks | ||
653 | |a adaptive gradient methods | ||
653 | |a stochastic gradient descent | ||
653 | |a bounded scheduling method | ||
653 | |a image classification | ||
653 | |a language modeling | ||
653 | |a texture | ||
653 | |a deep learning | ||
653 | |a MB-LBP | ||
653 | |a surface defect detection | ||
653 | |a feature extraction | ||
653 | |a defect recognition | ||
653 | |a mammogram | ||
653 | |a meta-heuristics | ||
653 | |a optimization | ||
653 | |a breast cancer | ||
653 | |a detection | ||
653 | |a skin microrelief | ||
653 | |a water sorption | ||
653 | |a aging | ||
653 | |a hair | ||
653 | |a mathematics of colour and texture | ||
653 | |a hand-designed image descriptors | ||
653 | |a rank features | ||
653 | |a partial orders | ||
653 | |a river scene segmentation | ||
653 | |a local binary pattern | ||
653 | |a hue variance | ||
653 | |a surface reflection | ||
653 | |a audio classification | ||
653 | |a dissimilarity space | ||
653 | |a siamese network | ||
653 | |a ensemble of classifiers | ||
653 | |a pattern recognition | ||
653 | |a animal audio | ||
653 | |a co-saliency | ||
653 | |a omnidirectional images | ||
653 | |a video saliency | ||
653 | |a visual saliency estimation | ||
653 | |a n/a | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/4523 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/76932 |7 0 |z DOAB: description of the publication |