Color image segmentation is a very emerging topic in current image processing research. An optimal technique for the same is always sought by the researchers of this field. In this paper, an efficient approach for color image segmentation is proposed. Here, the input color image is first converted from RGB to HSV color space. The V channel of the HSV converted image is extracted and normalized between 0 and 1. Then this normalized V channel is sent as input to Fuzzy C Means (FCM) algorithm. The fuzzy segmented image is then thresholded with Otsu’s method. The thresholded image is then filtered by sobel filter and sent as input to the Meyer’s watershed algorithm. This produces the final segmented image of the original color image. The proposed approach is found very efficient after analyzing and comparing the results with previously existed watershed algorithm in terms of the MSE and PSNR values.