Face Detection Based on Skin Color Segmentation Using Fuzzy Entropy

Francisco Pujol,Antonio Jimeno-Morenilla,Mar Pujol,María Pujol

doi:10.3390/e19010026

Abstract

Face detection is the first step of any automated face recognition system. One of the most popular approaches to detect faces in color images is using a skin color segmentation scheme, which in many cases needs a proper representation of color spaces to interpret image information. In this paper, we propose a fuzzy system for detecting skin in color images, so that each color tone is assumed to be a fuzzy set. The Red, Green, and Blue (RGB), the Hue, Saturation and Value (HSV), and the YCbCr (where Y is the luminance and Cb,Cr are the chroma components) color systems are used for the development of our fuzzy design. Thus, a fuzzy three-partition entropy approach is used to calculate all of the parameters needed for the fuzzy systems, and then, a face detection method is also developed to validate the segmentation results. The results of the experiments show a correct skin detection rate between 94% and 96% for our fuzzy segmentation methods, with a false positive rate of about 0.5% in all cases. Furthermore, the average correct face detection rate is above 93%, and even when working with heterogeneous backgrounds and different light conditions, it achieves almost 88% correct detections. Thus, our method leads to accurate face detection results with low false positive and false negative rates.

Highlights

In recent years, there has been intensive research to develop complex security systems involving biometric features
This article has presented a review of different skin detection algorithms on color images, having studied the main features of the most common color spaces: RGB, HSV and YCbCr
A proposal of fuzzy skin color detectors for these color spaces has been discussed throughout this work

Summary

Introduction

There has been intensive research to develop complex security systems involving biometric features. A biometric system is a pattern recognition system that makes a personal identification by determining the authenticity of a specific physiological or behavioral characteristic possessed by the user. One of the most popular biometric techniques to identify users is face recognition. An automatic face recognition system is based on extracting a set of features from the user’s face, either geometric characteristics or some information of textures and shapes of the different elements that constitute a human face. Before a recognition algorithm is applied, faces must have been detected in an image using some detection method. Detecting a face is the first step for the recognition process to be efficiently completed

Results

Discussion

Conclusion