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Proceedings Paper

Textured images classification in the JPEG domain
Author(s): Kh. Manglem Singh; P. K. Bora; S. Birendra Singh
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Paper 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.

Paper Details

Date Published: 24 September 2001
PDF: 6 pages
Proc. SPIE 4554, Object Detection, Classification, and Tracking Technologies, (24 September 2001); doi: 10.1117/12.441643
Show Author Affiliations
Kh. Manglem Singh, Indian Institute of Technology (India)
P. K. Bora, Indian Institute of Technology (India)
S. Birendra Singh, Ctr. for Electronics Design and Technology of India (India)

Published in SPIE Proceedings Vol. 4554:
Object Detection, Classification, and Tracking Technologies
Jun Shen; Sharatchandra Pankanti; Runsheng Wang, Editor(s)

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