Recently medical cosmetic has attracted significant business opportunity. Micro cosmetic surgery usually involves invasive cosmetic procedures such as non-ablative laser procedure for skin rejuvenation. However, to select an appropriate treatment for skin relies on accurate preoperative evaluations. In this paper, an automatic facial skin defects detection and recognition method is proposed. The system first locates the facial region from the input image. Then, the shapes of faces were recognized using a contour descriptor. The facial features are extracted to define regions of interest and an image segment method is used to extract potential defect. A support-vector-machine-based classifier is then used to classify the potential defects into spots, acnes and normal skin. Experimental results demonstrate effectiveness of the proposed method.

Recently medical cosmetology has attracted significant business opportunity. Micro cosmetic surgery usually involves the minimally invasive cosmetic procedures such as non-ablative laser procedure for skin rejuvenation. However, an appropriate treatment selection for skin relies on accurate preoperative evaluation. In this paper, an automatic facial skin defects detection and recognition system is proposed. The system automatic locates the facial region and extracts region of interest. A support-vector-machine-based classifier is then used to classify the potential defects into spot, acne and normal skin. Experimental results demonstrate effectiveness of the proposed approach.

No abstract