Title :
A classification-driven partially occluded object segmentation (CPOOS) method with application to chromosome analysis
Author :
Lerner, Boaz ; Guterman, Hugo ; Dinstein, Its´Hak
Author_Institution :
Comput. Lab., Cambridge Univ., UK
fDate :
10/1/1998 12:00:00 AM
Abstract :
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
Keywords :
cellular biophysics; image classification; image resolution; image segmentation; medical image processing; CPOOS method; chromosome analysis; classification-driven partially occluded object segmentation method; concavity; human cell images; segment images; Biological cells; Image analysis; Image resolution; Image segmentation; Layout; Object detection; Object segmentation; Signal analysis; Signal detection; Signal processing;
Journal_Title :
Signal Processing, IEEE Transactions on
