Multi-Human Face Detection Using Gabor Filters and Neural Networks in Internet Images
Subject Areas : electrical and computer engineering
R.
Mohammadian
1
(دانشگاه آزاد اسلامی، واحد كاشان)
M.
Mahlouji
2
Keywords: Gabor energy vertical projection median filter facial feature,
Abstract :
This paper presents a new method for multi human face detection from frontal view in internet images with complex background. The main goal is to reduce false acceptance error rate using feed forward back propagation multilayer perceptron neural network and Gabor energy feature in the frequency domain. In the proposed method, the false acceptance error extremely decreased using a combination of three operations; introducing a new preprocessing algorithm to increase the quality of Gabor energy feature, performing two step monitoring on the input and output images, and utilizing three indexes of facial components recognition in Gabor energy output. In this paper, a new image database namely RFD is collected from internet images including 583 non repetitive face images and 9961 non face images with size of 192×168. The face detection accuracy of the proposed method on RFD images is 88.16% with false acceptance rate of 0.48% or 48 false acceptances only, while Viola-Jones algorithm has 124 false acceptances. Therefore, the false acceptance error of the proposed method has reduced by 2.5 times compared to that of Viola-Jones algorithm.
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