A classification-driven partially occluded object segmentation (CPOOS) method with application to chromosome analysis

摘要

Classification of segment images created by connecting points of high concavity along curvatures is used to resolve partial occlusion in images. Modeling of shape or curvature is not necessary nor is the traditional excessive use of heuristics. Applied to human cell images, 82.6% of the analyzed clusters of chromosomes are correctly separated, rising to 90.5% following rejection of 8.7% of the images.