COLOR IMAGE SEGMENTATION BASED ON JND COLOR HISTOGRAM

This paper proposes a new color image segmentation algorithm based on the JND (Just Noticeable Difference) histogram. Histogram of the given color image is computed using JND color model. This samples each of the three axes of color space so that just enough number of visually different color bins (each bin containing visually similar colors) are obtained without compromising the visual image content. The number of histogram bins are further reduced using agglomeration successively. This merges similar histogram bins together based on a specific threshold in terms of JND. This agglomerated histogram yields the final segmentation based on similar colors. The performance of the proposed algorithm is evaluated on Berkeley Segmentation Database. Two significant criteria namely PSNR and PRI (Probabilistic Rand Index) are used to evaluate the performance. Results show that the proposed algorithm gives better results than conventional color histogram (CCH) based method and with drastically reduced time complexity.