Abstract: Facial retouching is widely used in media and entertainment industry. Professional software usually require a minimum level of user expertise to achieve the desirable results. In this present an algorithm to detect facial wrinkles/imperfection. Here believe that any such algorithm would be amenable to facial retouching applications. The detection of wrinkles/imperfections can allow these skin features to be processed differently than the surrounding skin without much user interaction. For detection, bilateral filter responses along with texture orientation field are used as image features. A bimodal Gaussian mixture model (GMM) represents distributions of Gabor features of normal skin versus skin imperfections, GMM distributions and texture orientations. An expectation-maximization algorithm then classifies skin versus skin wrinkles/imperfections. Once detected manually, wrinkles/imperfections are removed completely instead of being blended or blurred. Here it propose an exemplar-based constrained texture synthesis algorithm to inpaint irregularly shaped gaps left by the removal of detected wrinkles/imperfections. And it presents results conducted on images downloaded from the Internet to show the efficacy of our algorithms.
Keywords: Facial wrinkles, skin imperfections, Markov random field, Gaussian mixture model, bilateral features, texture orientation fields.