Enhanced Color Image Segmentation by Graph Cut Method in General and Medical Images

Segmentation of color images is a tricky task. Regaining the segments in an image using the content image is a difficult and significant problem. Medical imaging is the most alive research topic from the past two decades. From the medical diagnosis of patients suffering from various diseases, abnormal regions in the organs can be easily identified, which is a greatest achievement. It is experimentally proved that graph based segmentation methods are better than the other segmentation techniques, especially when combined with statistical methods. We have proposed color image segmentation by adaptive graph cut method in this paper. It consists of two important stages. During the first phase we enhance the input color image using transformation technique as the image may contain noise, may be of low contrast and missing some color statistics. Then this enhanced color image is processed under graph cut technique to get better results, especially for the analysis of medical and general images. The proposed method contributes to medical imaging by means of image segmentation and also to other general image analysis. Our experimental results are found to very good in segmenting color images.