Video Segmentation Using Hierarchical Merge Tree is analyzed in this paper by means of fast fuzzy c-means clustering algorithm and fuzzy membership function. Proposed work is completed for the color segmentation, as previous research presents a connected coherence tree algorithmic rule (CCTA) for Video segmentation with no prior information. It aims to search out regions of semantic coherence based on the projected ɛ-neighbor coherence segmentation criterion. Rgb Video is converted to Lab color space by taking average of each color component individually, then the average value of the color of small region selected is compared with all the pixels of the Video and finally the desired object gets segmented efficiently. This algorithm runs in small time with much accuracy since, FFCM avoids some unnecessary comparisons between the pixels.