Mathematical model for reduction of the probable spectrum of skin tones in the RGB color space for application in robotic vision with face detection
Abstract
Skin detection techniques are widely applied to locate and track the human body for the purpose of further recognition. Some advantages of face detection based on skin color in relation to other techniques are the smallest processing time and the angle of rotation invariance and semi-occlusion of faces. Numerous researches have been done with the aim of increasing the capacity perception of the environment by robotic devices using computer vision. In this article are presented theresults of a survey that investigated the reduction in the amplitude of spectrum of colors in the RGB system for detecting skin with possible application in robotic systems developed for tracking and recognition of people. Applied to 16,777,216 possible combinations of colors in the RGB system the 6 rules considered relevant bythe proposed mathematical model allowed a 98.3657% reduction of the spectrum. Experimental results prove the accuracy method considering only 1.6343% (253,159) of colors as candidates for human skin tones and a high rate of correct classification in tests on images of database FDDB.
Text in Portuguese, Original Title: Modelo matematico para reducao do espectro provavel de tons de pele no espaco de cores RGB para aplicacao em visao robotica com deteccao de face.
Fabrizzio Soares
Associate Professor and CS Chair
Fabrizzio Soares is a professor of Computer Science, Information Systems and Software Engineering at INF/UFG. His research interests include Computer Vision, Human Computer Interaction, Machine Learning and Programming topics. He is the leader of the Pixellab group, which develops solutions for accesibilty, Precision Agriculture, and Interactive Systems.