Analysis of Image Segmentation Methods Based on Performance Evaluation Parameters
Monika Xess ., S. Akila Agnes · 2014
Image segmentation is an important technology for image processing which aims at partitioning the image into different homogeneous regions or clusters. Lots of general-purpose techniques and algorithms have been developed and widely applied in various application areas. However, evaluation of these segmentation algorithms has been highly subjective and a difficult task to judge its performance based on intuition. In this paper image segmentation using FCM, Region Growing and Watershed algorithms is performed and segmentation results of these techniques are analyzed based on four performance metrics GCE, PSNR, RI and VoI. This analysis provides an overview that on what parameters different image segmentation techniques can be evaluated at best.