Overview

Texture analysis is an important generic research area of machine vision. The potential areas of application include biomedical image analysis, industrial inspection, analysis of satellite or aerial imagery, content-based retrieval from image databases, document analysis, biometric person authentication, scene analysis for robot navigation, texture synthesis for computer graphics and animation, and image coding. Texture analysis has been a topic of intensive research for over three decades, but the progress has been very slow.A workshop on Texture Analysis in Machine Vision was held at the University of Oulu, Finland, in 1999, providing a forum for presenting recent research results and for discussing how to make progress in order to increase the usefulness of texture in practical applications. This book contains extended and revised versions of the papers presented at the workshop. The first part of the book deals with texture analysis methodology, while the second part covers various applications. The book gives a unique view of different approaches and applications of texture analysis. It should be of great interest both to researchers of machine vision and to practitioners in various application areas.Contents: Nonparametric Texture Analysis with Complementary Spatial Operators (M Pietikainen & T Ojala) Multi-Resolution Clustering of Texture Images (S Battiato & G Gallo) Robustness of Local Binary Pattern (LBP) Operators to Tilt-Compensated Textures (M Soriano et al.) Using Texture in Image Similarity and Retrieval (S Aksoy & R M Haralick) Tongue Texture Analysis Using Gabor Wavelet Opponent Colour Features for Tongue Diagnosis in Traditional Chinese Medicine (P C Yuen et al.) Feature Evaluation of Texture Test Objects for Magnetic Resonance Imaging (A Materka et al.) Automatic Detection of Errors on Textures Using Invariant Grey-Scale Features and Polynomial Classifiers (M Schael & H Burkhardt) Combining Analysis and Synthesis of Textures for the Animation Industry (M Ollila et al.) and other papersReadership: Researchers, graduate students and industrialists in the field of machine vision.

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9781299609594

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