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Paper on Technologies used for Interactive Image Segmentation

Image segmentation is the process that partitions an image into region. Although many literatures studied automated image segmentation, it is still difficult to segment region-of-interest in any kind of images. Thus, manual delineation is important yet. [2] In order to shorten the processing time and to decrease the effort of users, this paper introduces the approaches of interactive image segmentation method based on various technologies. Interactive segmentation aims to separate an object of interest from the rest of an image. This problem in computer vision is known to be hard, and very few fully automatic vision systems exist which have been shown to be accurate and robust under all sorts of challenging inputs. Most of the previous works require users to trace the whole boundary of the object. When the object has a complicated boundary, or the object is in a highly textured region, users have to put great effort into iteratively correcting the selection. [1] This paper presents the study of different interactive image segmentation technologies for image foreground background separation. Various technologies used for interactive image segmentation are Adaptive GMMRF model, Maximal similarity based region merging, Probabilistic hypergraphs, Intelligent scissors, Adaptive weighted distances, Interactive graph cut method based on improved Gabor features, Constrained laplacian optimization, Dirichlet process multiple view learning (DPMVL) etc. Dirichlet Process Multiple-View Learning (DPMVL) for image segmentation technique produces very effective segmentation results as compare to previously existing techniques. DPMVL use MRF model for smoothing the segmentation. This can be further improved by using another effective technology by adding some new features which will work effectively and provide an alternative computational algorithm for building interactive image editing tools. We have the chances to improve the DPMVL image segmentation technique by using modified technology which will have more interactivity, user control of segmentation process, and reach a satisfied result among the noise restraint, edge preservation and computation complexity. Keywords— Image Processing, Image segmentation, Interactive image segmentation, DPMVL.