A Study on Segmentation of Bite Mark Images Using Chan-Vese Method and Canny Algorithm

Now a days, Bite mark investigation plays a vital area in forensic image processing, and is treated as a common way of dental proof offered in assisting criminal cases. The bite marks of suspects are compared with victim using the required measurements. This paper presents an effective bite mark investigation using Chan-vese segmentation. The proposed model includes two processes, specifically enhancement and segmentation. At the earlier stage, Contrast Limited Adaptive Histogram Equalization (CLAHE) is applied for image enhancement. Then, the processed image undergoes segmentation process by using Chan-vese method and Canny edge detection method. In this, Chan-vese method is more effective in detecting the edges of bite mark images whereas Canny algorithm is less effective in detecting the edges. Therefore Chan-vese method has an effective approach than Canny algorithm in detecting bite mark edges.