Texture and Colour in Image Analysis
Bianconi, Francesco
Texture and Colour in Image Analysis - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (278 p.)
Open Access
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.
Creative Commons
English
books978-3-0365-1377-5 9783036513782 9783036513775
10.3390/books978-3-0365-1377-5 doi
Information technology industries
Machine vision image analysis item counting device electro-deposition industry digital intraoral radiography image preprocessing periapical lesions texture analysis prostate cancer histopathology microscopic tissue image segmentation morphological quantitative classification SVM image resizing local Tchebichef moments (LTM) scaling scale-and-stretch seam carving faster R-CNN cutting pieces multi-period pattern skew angle period length colored texture pattern classification global–local texture classification color–texture features color–texture feature extraction bagging post-processing BQMP and Haralick global–local feature integration maceral components image segmentation coal petrography random forest two-level clustering deep neural networks adaptive gradient methods stochastic gradient descent bounded scheduling method image classification language modeling texture deep learning MB-LBP surface defect detection feature extraction defect recognition mammogram meta-heuristics optimization breast cancer detection skin microrelief water sorption aging hair mathematics of colour and texture hand-designed image descriptors rank features partial orders river scene segmentation local binary pattern hue variance surface reflection audio classification dissimilarity space siamese network ensemble of classifiers pattern recognition animal audio co-saliency omnidirectional images video saliency visual saliency estimation n/a
Texture and Colour in Image Analysis - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 - 1 electronic resource (278 p.)
Open Access
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.
Creative Commons
English
books978-3-0365-1377-5 9783036513782 9783036513775
10.3390/books978-3-0365-1377-5 doi
Information technology industries
Machine vision image analysis item counting device electro-deposition industry digital intraoral radiography image preprocessing periapical lesions texture analysis prostate cancer histopathology microscopic tissue image segmentation morphological quantitative classification SVM image resizing local Tchebichef moments (LTM) scaling scale-and-stretch seam carving faster R-CNN cutting pieces multi-period pattern skew angle period length colored texture pattern classification global–local texture classification color–texture features color–texture feature extraction bagging post-processing BQMP and Haralick global–local feature integration maceral components image segmentation coal petrography random forest two-level clustering deep neural networks adaptive gradient methods stochastic gradient descent bounded scheduling method image classification language modeling texture deep learning MB-LBP surface defect detection feature extraction defect recognition mammogram meta-heuristics optimization breast cancer detection skin microrelief water sorption aging hair mathematics of colour and texture hand-designed image descriptors rank features partial orders river scene segmentation local binary pattern hue variance surface reflection audio classification dissimilarity space siamese network ensemble of classifiers pattern recognition animal audio co-saliency omnidirectional images video saliency visual saliency estimation n/a