ILUT based Skin Colour Modelling for Human Detection

Objectives: Numerous techniques have been proposed in past for skin colour modelling and some out of these are utilized in human detection problem. This paper proposes a novel technique which uses Indexed Look-up-table (ILUT) for skin colour modelling. Methods: In the proposed technique, skin colour cluster on 2-dimensional Cb-Cr plane in YCbCr colour space is modelled with an ILUT. ILUT contains the lower and upper bounds of Cb values corresponding to each value of Cr in the skin colour cluster. Outliers in the cluster are removed by applying median filter, because they contribute to the wrong classification of skin colour and hence wrong detection. Findings: The proposed technique delivers reasonably good performance on True Positive Rate (TPR), False Positive Rate (FPR) and Accuracy parameters. Classification accuracy of 89.89% for proposed technique is almost comparable to that of other techniques in literature. Comparative results are shown in Table 2 of the paper. Classification complexity is one parameter on which the proposed technique outperforms the rest of the other skin colour modelling techniques and it is of O(MxN). MxN is the image resolution. Skin colour modelling using ILUT is also efficient in terms of space requirements as compared to other non-parametric methods of skin colour modelling. Applications: Least classification complexity makes this technique most appropriate for real time systems/ applications for detecting presence of human being.