Textured images classification in the JPEG domain

Kh. Manglem Singh; P. K. Bora; S. Birendra Singh

doi:10.1117/12.441643

24 September 2001 Textured images classification in the JPEG domain

Kh. Manglem Singh, P. K. Bora, S. Birendra Singh

Proceedings Volume 4554, Object Detection, Classification, and Tracking Technologies; (2001) https://doi.org/10.1117/12.441643
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China

Abstract

In this paper, we present a novel approach to the classification of texture images in the JPEG domain using the hard and soft thresholding functions, avoiding the need of the various stages of the decompression. A texture block of 8X8 size in discrete cosine transform (DCT) form is assigned to the most similar and nearest cluster center, where the shortest distance is selected from the list of distances of the blocks of the texture from the different cluster centers, that have been already calculated using fuzzy learning vector quantization (FLVQ), in which means and variances of AC energy of DCT blocks are inputs.

Citation Download Citation

Kh. Manglem Singh, P. K. Bora, and S. Birendra Singh "Textured images classification in the JPEG domain", Proc. SPIE 4554, Object Detection, Classification, and Tracking Technologies, (24 September 2001); https://doi.org/10.1117/12.441643

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