Biometrics systems based on ear are still in need of more investigation to make it robust and accurate. The most critical step in
ear recognition is segmentation as all subsequent steps will depend on the accuracy of segmentation. In this paper, Box counting
segmentation method is suggested. The proposed method consists of a sequence of steps. First, a Normalized Cuts method is
applied to initiate the ear image segmentation process. Then, the segmentation process is perfected by performing the following
functions gray-level slicing, entropy, thresholding, skeletonization, image filling and opening. Finally, a substitution process is
applied. Our proposed algorithms are tested on ear images captured produced encouraging result. A 95 percent accuracy rate is
achieved at an average of 10 seconds processing time.