Detecting facial features by heteroassociative memory neural network utilizing facial statistics

Authors:
Kyeong-Seop Kim;Tae-Ho Yoon;Seung-Won Shin
Affiliations:
School of Biomedical Engineering, College of Biomedical & Health Science, Konkuk University, Chungju, Korea;School of Biomedical Engineering, College of Biomedical & Health Science, Konkuk University, Chungju, Korea;School of Biomedical Engineering, College of Biomedical & Health Science, Konkuk University, Chungju, Korea
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

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Abstract

In this paper, we present an efficient algorithm of extracting the multiple facial features such as eyes, nose, and mouth. The face candidates are first obtained based on skin-color filtering inYCbCr color domain and skin-temperature values and then the elliptic measures are applied to extract a true face candidate and its boundary. A Sobel edge mask is performed and consequently horizontal projection operation is applied to locate the eyes referring to the maximum horizontal projection value in Y component. Once two eyes are located, the distance that crosses the center of eyes and extends to the face boundary, D1 is determined. A heteroassociative memory neural network model is utilized to find the facial features. An input neuron vector X accepts D1 and the output neurons vector Y maps it to the facial features such as eyes, nose and mouth.