Region Merging Based Image Segmentation Using Maximal Similarity Mechanism

Image segmentation is the basic step in image Analysis and processing mechanism. The Image is partitioned into multiple segments so that a meaningful image is extracted out and then image is analyzed easily. Many techniques have been developed for the Image segmentation and there has been a constant growth in the research area of image segmentation and with this it has become more important to provide the readers with the growing research on image segmentation, it has become important to categorize the research outcomes and provide readers with an overview of the existing segmentation techniques in each category. In this paper, different image segmentation techniques are reviewed and presents a new region merging based interactive image segmentation method. A novel maximal similarity based region merging mechanism is used to guide the merging process with the help of markers and applying weighted sum method thatautomatically merges the regions that are initially segmented by mean shift segmentation, and then effectively extracts the object contour by labeling all the non-marker regions as either background or foreground and then to predict TPR and FPR for proposed algorithm.