In this paper, some transition region based segmentation approaches have developed to perform image segmentation for grayscale and colour images. In 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 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, efficient and effective transition regions based on threshold filter approaches for image segmentation for both grayscale and colour images.

Image Segmentation, False Positive Rate (FPR), False Negative Rate (FNR), Misclassification Error (ME)

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