Abstract
There are always two main problems in identification of human beings through their ear images: 1- If distances of the individual from camera changes, the sizes of ears in the saved images are varied in proportion to this distance. 2- If head of people in taken images is tilted upwards or downwards, this causes ear images of these people rotate in proportion to saved ear images in database. In both of these cases, all identification systems do not work properly. In this article, we proposed a new method for normalizing human ear images by detecting the rotation and scaling variation, and normalizing the ear images accordingly. Our proposed method works well on all ear databases and all ear images (either left or right) which have been taken from front side of the ears. Our method provides high performance to the biometric identification systems to identify human being, even when the images of human ears are taken from long distance with small scale.
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Yazdanpanah, A.P., Faez, K. (2009). Normalizing Human Ear in Proportion to Size and Rotation. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2009. Lecture Notes in Computer Science, vol 5754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04070-2_5
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DOI: https://doi.org/10.1007/978-3-642-04070-2_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04069-6
Online ISBN: 978-3-642-04070-2
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