Development of transition region based methods for image segmentation

Abstract

In this thesis, some transition region based segmentation approaches have developed to perform image segmentation for grayscale and colour images. newlineIn computer vision and image understanding applications, image segmentation is an important pre-processing step. The main goal of the segmentation process is the separation of foreground region from background region. Based on the output of the segmentation result, segmentation can be categorized as global segmentation or local segmentation. The global segmentation aims for complete separation of the object from the background while the local segmentation divides the image into constituent regions. For achieving segmentation, a number of algorithms are developed by various researchers. The segmentation approaches are application specific and do not work well for both grayscale and colour image segmentation. For any image consisting of foreground and background, some transition regions exist between the foreground and background regions. Effective extraction of transition region leads to a better segmentation result. Therefore, the doctoral thesis intends to efficient and effective transition region approaches for image segmentation for both grayscale and colour images. newline