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Hand motion segmentation against skin colour background in breast awareness applications.

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  • 1BIOCORE, School of Mathematical and Information Sciences, Coventry University, Coventry, UK.


Skin colour modelling and classification play significant roles in face and hand detection, recognition and tracking. A hand is an essential tool used in breast self-examination, which needs to be detected and analysed during the process of breast palpation. However, the background of a woman's moving hand is her breast that has the same or similar colour as the hand. Additionally, colour images recorded by a web camera are strongly affected by the lighting or brightness conditions. Hence, it is a challenging task to segment and track the hand against the breast without utilising any artificial markers, such as coloured nail polish. In this paper, a two-dimensional Gaussian skin colour model is employed in a particular way to identify a breast but not a hand. First, an input image is transformed to YCbCr colour space, which is less sensitive to the lighting conditions and more tolerant of skin tone. The breast, thus detected by the Gaussian skin model, is used as the baseline or framework for the hand motion. Secondly, motion cues are used to segment the hand motion against the detected baseline. Desired segmentation results have been achieved and the robustness of this algorithm is demonstrated in this paper.

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