ANALYSIS OF COLOR IMAGE ENHANCEMENT IN MORPHOLOGICAL BASED WATERSHED SEGMENTATION
Thida Soe, Soe Soe Mon, Khin Aye Thu · International journal of advance research and innovative ideas in education · 2019
Color image segmentation is the area of color image analysis and pattern recognition. Many segmentation algorithms have been developed for this purpose. But, the segmentation results of these algorithms seem to be suffering from miss-classifications and over-segmentation. The reasons behind these are the degradation of image qualities during the acquisition, transmission and color space conversion. So, here arises the need of an efficient image enhancement technique which can remove the redundant pixels or noises from the color image before proceeding for final segmentation. In this paper, an effort has been made to study and analyze image enhancement techniques for morphological based watershed segmentation. Firstly, the input RGB images are converted to HSV, L*a*b and YCbCr color space models because these color spaces are more suitable for color image segmentation. In HSV, only V channel, in L*a*b, only L (luminance) channel and in YCbCr, all components(Y, Cb, Cr) are applied in histogram equalization for image enhancement, respectively. And then, replacing the original channels with the histogram equalized enhanced channel. Morphological based watershed segmentation technique is used to segment the enhanced images. Finally, their comparative study is done on three color spaces separately to find out which color space supports segmentation task more efficiently with respect to these enhancement techniques.