<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Human face detection is an indispensable component in face processing applications, including automatic face recognition, security surveillance, facial expression recognition, and the like. This paper presents a profile face detection algorithm based on curvelet features, as curvelet transform offers good directional representation and can capture edge information in human face from different angles. First, a simple skin color segmentation scheme based on HSV (Hue - Saturation - Value) and YCgCr (luminance - green chrominance - red chrominance) color models is used to extract skin blocks. The segmentation scheme utilizes only the S and CgCr components, and is therefore luminance independent. Features extracted from three frequency bands from curvelet decomposition are used to detect face in each block. A support vector machine (SVM) classifier is trained for the classification task. In the performance test, the results showed that the proposed algorithm can detect profile faces in color images with good detection rate and low misdetection rate</p>
</abstract>

Human face detection is an indispensable component in face processing applications, including automatic face recognition, security surveillance, facial expression recognition, and the like. This paper presents a profile face detection algorithm based on curvelet features, as curvelet transform offers good directional representation and can capture edge information in human face from different angles. First, a simple skin color segmentation scheme based on HSV (Hue - Saturation - Value) and YCgCr (luminance - green chrominance - red chrominance) color models is used to extract skin blocks. The segmentation scheme utilizes only the S and CgCr components, and is therefore luminance independent. Features extracted from three frequency bands from curvelet decomposition are used to detect face in each block. A support vector machine (SVM) classifier is trained for the classification task. In the performance test, the results showed that the proposed algorithm can detect profile faces in color images with good detection rate and low misdetection rate

Face Detection In Profile Views Using Fast Discrete Curvelet Transform (Fdct) And Support Vector Machine (Svm)

Faculty of Electrical Engineering, Universiti Teknologi Malaysia (UTM)

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Human face detection is an indispensable component in face processing applications, including automatic face recognition, security surveillance, facial...

Face Detection In Profile Views Using Fast Discrete Curvelet Transform (Fdct) And Support Vector Machine (Svm)

Publié en ligne: 01 mars 2016

Pages: 108 - 123

Reçu: 03 nov. 2016

Accepté: 12 janv. 2016

DOI: https://doi.org/10.21307/ijssis-2017-862

Mots clés
face detection, curvelet transform, HSV, YCgCr, SVM

© 2016 Bashir Muhammad et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Face Detection In Profile Views Using Fast Discrete Curvelet Transform (Fdct) And Support Vector Machine (Svm)

Publié en ligne: 01 mars 2016

Pages: 108 - 123

Reçu: 03 nov. 2016

Accepté: 12 janv. 2016

DOI: https://doi.org/10.21307/ijssis-2017-862

Mots clésface detection, curvelet transform, HSV, YCgCr, SVM

© 2016 Bashir Muhammad et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
face detection, curvelet transform, HSV, YCgCr, SVM