Region-based seed point cell segmentation and detection for biomedical image analysis

Salient region detection and segmentation from biological images is often a crucial step for image understanding. The initial contour selection during segmentation being a competent task and wrong differentiation between the foreground and background colours are compromised. In this paper, improved cell detection is introduced by using a region-based cell detection and segmentation method called Histogram Colour Contrast Seed Point Selection (HCC-SPS). In each pixel, the HCC model is able to group similar colour values, therefore addressing colour contrast in visual signal, resulting in accurate desired edge points. Second, considering the energy function, region-based seed point fine tunes the salient value and makes differentiation between salient and background points easier. Third, due to salient mapping function with pixel representation, the segmentation of biological images, done accurately. The results are compared with the existing system based on the parameters such as accuracy rate, segmentation time and mapping functions.