SEGMENTATION OF REGIONS IN JPEG COMPRESSED MEDICAL IMAGES (WP-P8)

Author(s) : Pramod Singh (School of Computer Science and Engineering, University of New South Wales, Australia)

Abstract : A novel algorithm for the segmentation of medical images using features derived directly from JPEG compressed domain is proposed in this paper. The algorithm uses features extracted from DCT coefficients without its inverse transform and the Rule based Fisher Discriminant K-means (FDK) technique for clustering image pixels based on derived feature vectors. In this study, we extract features for each 2x2 DCT block of compressed image. The DCT coefficients of 2x2 block are obtained from JPEG baseline compressed image. The extracted feature vector is used by a modified version of the adaptive K-means clustering algorithm for the classification of image pixels.

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