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| An Automatic Ear Detection Method Based on Improved GVF Snake |
| LI Yi-Bo1,HUANG Zeng-Xi1,ZHANG Hai-Jun1,MU Zhi-Chun2 |
1.College of Automation,Shenyang Aerospace University,Shenyang 110136
2.School of Information Engineering,University of Science and Technology Beijing,Beijing 100083 |
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Abstract In recent years the biological characteristic research of human ear can only rely on manual positioning and segmentation, which is one obstruction in the practice process of human ear recognition technology. A method of human ear automatic detection is presented in this paper. Firstly, it detects the human ear pieces by taking advantage of YCbCr Skin-Color Model and Gentle AdaBoost cascade classifier, and then uses the improved GVF Snake method to extract the external ear contour. The method extracts the initial contour very close to the actual edge of human ear by building up the ear-shaped map. Accordingly, it not only saves iteration time, but also improves the accuracy of external ear detection in way of GVF Snake. About 97.3% of the correct detection rate is obtained on USTB ear database in our experiment. The experiment results show that the approach has better detection performance and robustness.
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Received: 08 June 2009
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2010, Vol. 23 
