Segmentation of textured images using local spatial-frequency representation

Yue Tao

doi:10.1117/12.323231

1 October 1998 Segmentation of textured images using local spatial-frequency representation

Yue Tao

Proceedings Volume 3460, Applications of Digital Image Processing XXI; (1998) https://doi.org/10.1117/12.323231
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

This paper presents an algorithm for segmentation of textured images. The algorithm uses an unsupervised neural network and K-means method to classify image pixels based on image local spatial-frequency information. The short-time Fourier transform employs large size window function to extract more neighborhood information. The problems of introducing large size windows in classifying larger transient regions are also investigated. High segmentation resolution is obtained by an novel image extrapolation approach and a re-classification procedure for transient areas.

Citation Download Citation

Yue Tao "Segmentation of textured images using local spatial-frequency representation", Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); https://doi.org/10.1117/12.323231

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