Image segmentation is an important part of any image analysis process. Meyer’s Watershed algorithm is one of the classical algorithms used for this purpose. But, the results of this algorithm usually suffer from over segmentation problem. To solve this problem, in this paper a new approach for color image segmentation is presented. In this approach, first the input RGB image is converted into HSV one and then the V channel of the later has been extracted. The histogram of the extracted V channel has been equalized to enhance the hidden edges. Here, through experiments, we have found that together Otsu’s thresholding with Sobel Filter forms a better preprocessing step for an image than any of them alone. So, focusing on this fact, the resultant equalized image is thresholded with Otsu’s method and after that filtered by Sobel filter. The filtered image is then sent as input to the watershed algorithm which produces the final segmented image. The output found is free from the over segmentation. Also, the evaluated values of the other image quality metrics like AMBE, NAE, MSE and PSNR show the efficiency of the proposed approach.

Image Segmentation, Color Image Segmentation,Histogram Equalization, HSV Color Space, Otsu’s Method, Sobel Filter and Watershed Algorithm

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