Analysis of Random Projection & Live –Wire For Texture Extraction & Segmentation
Journal Title: IOSR Journals (IOSR Journal of Electrical and Electronics Engineering) - Year 2018, Vol 13, Issue 5
Abstract
Automatic image segmentation requires a certain degree of depth of work combining image clustering, feature extraction, statistical analysis and iterative feedback. Researchers have been using algorithms like Principal component analysis (PCA) combined with advanced feature extraction techniques like gray level co-occurrence integrated algorithm (GLCIA), along with maximal difference schemes (MDS), have been proposed by researchers, and provide good quality of semi-automatic segmentation. But in these techniques, user intervention is needed in at least 1 of the steps in order to get a proper output. This work proposes a RP-live wire based algorithm which optimizes the segmentation process, and removes the user intervention from the segmentation process in order to produce high quality segmented images with truly automatic segmentation. Our results demonstrate a 20% improvement in overall system speed and 10% improvement in segmentation accuracy when compared with traditional algorithms.
Authors and Affiliations
Pradnya A. Maturkar, M. A. Gaikwad
Keywords
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- EP ID EP406758
- DOI 10.9790/1676-1305020105.
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