Imaging of the skin to detect the signs of cancer becomes very common these days. A new noninvasive skin imaging method developed recently gives an informative image data about the skin tissue by collecting scattered polarized light reflected from a mole area. This method scans the polarization states by continuously rotating a linearly polarized light incident on the lesion and collecting the reflected sequence of images with a CCD camera. The two main wavelengths that were used in the study were 520nm (penetration is about 100μm) and 700nm (penetration is about 200μm). Methods developed in the past to diagnose suspicious moles were implemented to visual images. However, such methods cannot be employed directly to our images because of their different properties. In this paper, we analyze skin moles obtained from this system for the purpose of distinguishing cancerous from benign moles. First, we pre-process the mole image by de-noising, contrast enhancement and intensity-based segmentation of the mole region. Then, an automatic examination of the polarized images is carried out according to characteristics such as their symmetry, cross-image local contrasts and large-scale homogeneity.