Multi-Scale Skin Sample Approach for Dynamic Skin Color Detection: An Analysis

Skin detection is an important step in many computer vision applications. It has been employed in face detection, hand gesture recognition, illicit image filtering, steganography and content based image retrieval. This is due to the skin colour that attractive feature in detecting the skin in coloured image. In contrast, skin colour detection suffers in low accuracy due to colour properties between the real skin surface and the skin-like objects. Therefore, this paper proposes a dynamic skin colour detection using multi-scales online skin sampling approach. This dynamic skin colour detection involved two procedures for generating the dynamic threshold in colour spaces. Moreover, six colour spaces have been studied to find the best colour models for our proposed method. The first procedure is the online skin sampling that obtained directly from the face candidates to generate the dynamic threshold values of each studied colour spaces. Alongside with the first procedure, we obtained optimal scale for skin sample with 0.25, 0.2 reduction. Meanwhile, the second procedure known as skin pixel classification uses the dynamic threshold obtained from the first procedure to classify the skin in the image. We achieved a satisfactory result in term of precision, recall, accuracy and F₁. The experimental result shows that the proposed dynamic skin colour detection achieved good performance via YCr colour model.