Color Image segmentation using Similarity based Region merging and Flood Fill Algorithm

Image segmentation is an important task in image processing and computer vision. Image Segmentation is a technique that partitioned the digital image into many number of homogeneous regions or sets of homogeneous pixels. In this paper corporate frameworks for object retrieval using semi-automatic method for object detection because fully automatic segmentation is very hard for natural images. To improve the effectiveness of object retrieval a maximal similarity based region merging and flood fill technique is used. The users only need to roughly indicate the position and main features of the object and background, then any region will belong to non-label region or label region i.e. object or background then after which steps desired objects contour is obtained during the automatic merging of similar regions. A similarity based region merging mechanism is to guide the merging process with the help of mean shift technique. Any two or more regions are merged with its adjacent regions on the basis of maximal similarity method. The method automatically merges the regions that are initially segmented through initial segmentation technique, and then effectively extracts the object contour by merging regions.