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Frontal Face Detection using Haar Wavelet Coefficients and Local Histogram Correlation
Iwan Setyawan1, Ivanna K. Timotius2 & Andreas A. Febrianto
Department of Electronic & Computer Engineering,
Satya Wacana Christian University,
Jl. Diponegoro 52 – 60, Salatiga, Indonesia
Email: 1iwan.setyawan@ieee.org, 2ivanna_timotius@yahoo.com
Abstract. Face detection is the main building block on which all automatic systems dealing with human faces is built. For example, a face recognition system must rely on face detection to process an input image and determine which areas contain human faces. These areas then become the input for the face recognition system for further processing. This paper presents a face detection system designed to detect frontal faces. The system uses Haar wavelet coefficients and local histogram correlation as differentiating features. Our proposed system is trained using 100 training images. Our experiments show that the proposed system performed well during testing, achieving a detection rate of 91.5%.
Keywords: biometric, face detection, haar wavelet, local histogram correlation, image processing, pattern recognition
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