Skin and Non-Skin Region Detection Using Elliptical Modeling Method

The process begins by converting the input image from RGB color space to YCbCr format, where Y represents the luminance component, while Cb and Cr represent the chrominance components crucial for skin tone detection. The elliptical modeling method is then applied to classify skin and non-skin regions based on the distribution of pixel values in the Cb-Cr chromaticity plane, where skin tones typically cluster within a specific elliptical boundary defined by statistical models. For implementation, this involves calculating the Mahalanobis distance of each pixel's (Cb, Cr) coordinates to the pre-defined elliptical center and thresholding based on the elliptical equation parameters. During binarization processing, pixels identified as skin regions are set to white (value 255), while non-skin regions are set to black (value 0), creating a clear segmentation mask. Key functions would include color space conversion using matrix transformations, elliptical boundary evaluation through distance calculations, and threshold-based pixel classification. The final processed results are displayed for visual evaluation of the skin detection accuracy and segmentation quality, allowing for parameter tuning and performance assessment.