Christoph R. Malskies, Eva Eibenberger, and Elli Angelopoulou
We present an algorithm to recognize ethnic groups based on biologically justified features, such as melanin or hemoglobin concentrations. These biophysical features are extracted from skin reflectance spectra and allow, in contrast to technical features, a medical interpretation and intuitive rating of the recognition results. For this purpose, a physics-based light transport model for skin is required. We use an existing model based on Kubelka-Munk theory, which is physically accurate and computationally tractable. The evaluation of the ethnicity classification reveals that in comparison to an approach, directly based on the reflectance spectra, our proposed biophysical classification is slightly better. To reduce computation time we analyze the impact of spectral band reduction on the ethnicity classification and show that this can be achieved on the expense of only a small accuracy loss.
Categories and Subject Descriptors (according to ACM CCS): I.4.1 [Image Processing and Computer Vision]: Digitzation and Image Capture-Reflectance I.4.8 [Image Processing and Computer Vision]: Scene Analysis-Color