Automating snakes for multiple objects detection
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Statistical and wavelet based texture features for fish oocytes classification
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Dictionary learning in texture classification
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
Contourlet-based texture retrieval using a mixture of generalized gaussian distributions
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
Color texture analysis based on fractal descriptors
Pattern Recognition
Algorithms for the Automated Detection of Diabetic Retinopathy Using Digital Fundus Images: A Review
Journal of Medical Systems
Computer Methods and Programs in Biomedicine
Symptomatic vs. Asymptomatic Plaque Classification in Carotid Ultrasound
Journal of Medical Systems
Local phase quantization for blur-insensitive image analysis
Image and Vision Computing
Supervised texture classification using a novel compression-based similarity measure
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Understanding symptomatology of atherosclerotic plaque by image-based tissue characterization
Computer Methods and Programs in Biomedicine
Illuminant invariant descriptors for color texture classification
CCIW'13 Proceedings of the 4th international conference on Computational Color Imaging
International Journal of Computer Applications in Technology
Computer Methods and Programs in Biomedicine
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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.