An Innovative Skin Detection Approach Using Color Based Image Retrieval Technique
This work addresses skin detection for applications like face recognition and human tracking, but it appears incremental as it builds on existing CBIR methods.
The paper tackles the problem of skin detection in image processing by proposing a color-based image retrieval (CBIR) technique, which achieves high accuracy without sensitivity to illumination intensity and moving face orientation.
From The late 90th, "Skin Detection" becomes one of the major problems in image processing. If "Skin Detection" will be done in high accuracy, it can be used in many cases as face recognition, Human Tracking and etc. Until now so many methods were presented for solving this problem. In most of these methods, color space was used to extract feature vector for classifying pixels, but the most of them have not good accuracy in detecting types of skin. The proposed approach in this paper is based on "Color based image retrieval" (CBIR) technique. In this method, first by means of CBIR method and image tiling and considering the relation between pixel and its neighbors, a feature vector would be defined and then with using a training step, detecting the skin in the test stage. The result shows that the presenting approach, in addition to its high accuracy in detecting type of skin, has no sensitivity to illumination intensity and moving face orientation.