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Texture segmentation using wavelet transform
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DOI：10.1016/j.patrec.2003.08.005.png)
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Abstract
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Texture analysis such as segmentation and classification plays a vital role in computer vision and pattern recognition and is widely applied to many areas such as industrial automation, bio-medical image processing and remote sensing. This paper describes a novel technique of feature extraction for characterization and segmentation of texture at multiple scales based on block by block comparison of wavelet co-occurrence features. The performance of this segmentation algorithm is superior to traditional single resolution techniques such as texture spectrum, co-occurrences, local linear transforms, etc. The results of the proposed algorithm are found to be satisfactory. (C) 2003 Elsevier B,V. All rights reserved.
Keywords:
texture
texture segmentation
feature extraction
wavelet co-occurrence features
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