Texture analysis is one of the fundamental aspects of human vision by which we discriminate between surfaces and objects. In a similar manner, computer vision can take advantage of the cues provided by surface texture to distinguish and recognize objects. In computer vision, texture analysis may be used alone or in combination with other sensed features (e.g. color, shape, or motion) to perform the task of recognition. Either way, it is a feature of paramount importance and boasts a tremendous body of work in terms of both research and applications.Currently, the main approaches to texture analysis must be sought out through a variety of research papers. This collection of chapters brings together in one handy volume the major topics of importance, and categorizes the various techniques into comprehensible concepts. The methods covered will not only be relevant to those working in computer vision, but will also be of benefit to the computer graphics, psychophysics, and pattern recognition communities, academic or industrial.
Cited By
- Liu Y, Gao Y, Sadia N, Qi L and Dong J (2024). A Sketch-texture Retrieval Framework using Perceptual Similarity, Knowledge-Based Systems, 286:C, Online publication date: 28-Feb-2024.
- Yan Z, Wu Y, Luo D, Zhang C, Jin Q, Chen W, Wu Y, Chen X, Wang G and Mi H (2023). NaCanva: Exploring and Enabling the Nature-Inspired Creativity for Children, Proceedings of the ACM on Human-Computer Interaction, 7:MHCI, (1-25), Online publication date: 11-Sep-2023.
- de Melo Langoni V and Gonzaga A (2019). Evaluating dynamic texture descriptors to recognize human iris in video image sequence, Pattern Analysis & Applications, 23:2, (771-784), Online publication date: 1-May-2020.
- Nsimba C and Levada A Nonlinear Dimensionality Reduction in Texture Classification: Is Manifold Learning Better Than PCA? Computational Science – ICCS 2019, (191-206)
- Liu L, Chen J, Fieguth P, Zhao G, Chellappa R and Pietikäinen M (2019). From BoW to CNN, International Journal of Computer Vision, 127:1, (74-109), Online publication date: 1-Jan-2019.
- Vard A (2018). A new combination active contour model for segmenting texture image with low contrast and high illumination variations, Multimedia Tools and Applications, 77:15, (20021-20042), Online publication date: 1-Aug-2018.
- Mirhashemi A (2018). Introducing spectral moment features in analyzing the SpecTex hyperspectral texture database, Machine Vision and Applications, 29:3, (415-432), Online publication date: 1-Apr-2018.
- Fraj O, Ghozi R and Jaïdane-Saïdane M (2017). Audio texturedness indicator based on a direct and reverse short listening time analysis, Multimedia Tools and Applications, 76:24, (26177-26200), Online publication date: 1-Dec-2017.
- Kuppili V, Biswas M, Sreekumar A, Suri H, Saba L, Edla D, Marinhoe R, Sanches J and Suri J (2017). Extreme Learning Machine Framework for Risk Stratification of Fatty Liver Disease Using Ultrasound Tissue Characterization, Journal of Medical Systems, 41:10, (1-20), Online publication date: 1-Oct-2017.
- Marcolin F and Vezzetti E (2017). Novel descriptors for geometrical 3D face analysis, Multimedia Tools and Applications, 76:12, (13805-13834), Online publication date: 1-Jun-2017.
- Pourfard M, Abdollahifard M, Faez K, Motamedi S and Hosseinian T (2017). PCTO-SIM, Computers & Geosciences, 102:C, (116-138), Online publication date: 1-May-2017.
- Fahmi H, Zen R, Sanabila H, Nurhaida I and Arymurthy A Feature Selection and Reduction for Batik Image Retrieval Proceedings of the Fifth International Conference on Network, Communication and Computing, (47-52)
- Boudra S, Yahiaoui I and Behloul A A Comparison of Multi-scale Local Binary Pattern Variants for Bark Image Retrieval Proceedings of the 16th International Conference on Advanced Concepts for Intelligent Vision Systems - Volume 9386, (764-775)
- Shrivastava V, Londhe N, Sonawane R and Suri J (2015). Exploring the color feature power for psoriasis risk stratification and classification, Computers in Biology and Medicine, 65:C, (54-68), Online publication date: 1-Oct-2015.
- Hiremath P and Bhusnurmath R RGB - Based Color Texture Image Classification Using Anisotropic Diffusion and LDBP Proceedings of the 8th International Workshop on Multi-disciplinary Trends in Artificial Intelligence - Volume 8875, (101-111)
- Dong X, Methven T and Chantler M How Well Do Computational Features Perceptually Rank Textures? A Comparative Evaluation Proceedings of International Conference on Multimedia Retrieval, (281-288)
- Acharya U, Sree S, Muthu Rama Krishnan M, Krishnananda N, Ranjan S, Umesh P and Suri J (2013). Automated classification of patients with coronary artery disease using grayscale features from left ventricle echocardiographic images, Computer Methods and Programs in Biomedicine, 112:3, (624-632), Online publication date: 1-Dec-2013.
- Cusano C, Napoletano P and Schettini R Illuminant Invariant Descriptors for Color Texture Classification Proceedings of the 4th International Workshop on Computational Color Imaging - Volume 7786, (239-249)
- Gangeh M, Ghodsi A and Kamel M Supervised Texture Classification Using a Novel Compression-Based Similarity Measure Proceedings of the International Conference on Computer Vision and Graphics - Volume 7594, (379-386)
- Rahtu E, Heikkilä J, Ojansivu V and Ahonen T (2012). Local phase quantization for blur-insensitive image analysis, Image and Vision Computing, 30:8, (501-512), Online publication date: 1-Aug-2012.
- Acharya R, Faust O, Alvin A, Sree S, Molinari F, Saba L, Nicolaides A and Suri J (2012). Symptomatic vs. Asymptomatic Plaque Classification in Carotid Ultrasound, Journal of Medical Systems, 36:3, (1861-1871), Online publication date: 1-Jun-2012.
- Allili M and Baaziz N Contourlet-based texture retrieval using a mixture of generalized gaussian distributions Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II, (446-454)
- Gangeh M, Ghodsi A and Kamel M Dictionary learning in texture classification Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I, (335-343)
- González-Rufino E, Carrión P, Formella A, Fernández-Delgado M and Cernadas E Statistical and wavelet based texture features for fish oocytes classification Proceedings of the 5th Iberian conference on Pattern recognition and image analysis, (403-410)
- Saha B, Ray N and Zhang H Automating snakes for multiple objects detection Proceedings of the 10th Asian conference on Computer vision - Volume Part III, (39-51)
Index Terms
- Handbook of Texture Analysis