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Research Article Open Access
This paper mainly concentrates on image segmentation using Wavelet, otsu and Curvelet algorithm. The existing Chan Vese model becomes complex in determining multiple images simultaneously in varying intensities. In order to increase the detection performance the WOC (wavelet Otsu curvelet) algorithm is proposed. Due to high directionality and anisotropic nature of the curvelet transform, it gives better performance at the edges and it is also applied for multi-scale edge enhancement. Wavelet transform is well suited for multi resolution. Wavelet and curvelet transforms are incorporated for sub band decomposition of frequency coefficients. Otsu algorithm has a novel approach for segmentation where thresholding is done using histogram analysis. This in turn reduces the segmentation complexity and hence the new algorithm is termed as Hybrid fast WOC algorithm.
Wavelet, Curvelet, Ridgelet, Histogram, OTSU, Segmentation, Functional Genomics,Genetic Probes