A taxonomy for texture description and identification
A central issue in computer vision is the problem of signal to symbol transformation. In the case of texture, which is an important visual cue, this problem has hitherto received very little attention. This book presents a solution to the signal to symbol transformation problem for texture. The symbolic de- scription scheme consists of a novel taxonomy for textures, and is based on appropriate mathematical models for different kinds of texture. The taxonomy classifies textures into the broad classes of disordered, strongly ordered, weakly ordered and compositional. Disordered textures are described by statistical mea- sures, strongly ordered textures by the placement of primitives, and weakly ordered textures by an orientation field. Compositional textures are created from these three classes of texture by using certain rules of composition. The unifying theme of this book is to provide standardized symbolic descriptions that serve as a descriptive vocabulary for textures. The algorithms developed in the book have been applied to a wide variety of textured images arising in semiconductor wafer inspection, flow visualization and lumber processing. The taxonomy for texture can serve as a scheme for the identification and description of surface flaws and defects occurring in a wide range of practical applications.
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Computing oriented texture fields
The analysis of oriented textures through phase portraits
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affine transformations analysis analyze angle and coherence angle histogram applying the orientation approach chapter classified co-occurrence coherence image coherence map compositional textures computer vision defect defined derived describe descriptors differential equations direction disordered texture edge detection Filter sizes flow field flow image flow-like textures fractal dimension frieze groups frieze pattern Gaussian filter given texture glide reflection gradient vectors gray levels histogram Illustrating intrinsic images Kass and Witkin knots least squares line segments located at following matrix method models non-linear least squares obtained optical flow orientation estimation algorithm orientation field overlayed oriented textures original image original texture phase portraits pixels placement rules presented primitive textures problem reconstructed region result of applying rotation saddle fixed points scale scheme shown in figure singular spiral fixed points strongly ordered textures structural surface symbolic description taxonomy for texture techniques tion transformation vector field vortices wafer wallpaper groups weakly ordered texture