Abstract

This paper presents the ear shape permanence study. The main purpose of this study is to determine the permanence of the ear shape and when does the ear stop developing. This is done by comparing ear recognition methods using images affected by illumination and geometrical changes. However, current work determine the most suitable method that can be used for ear recognition of young children that still under-go different geometrical changes and skin complexion changes. Therefore, suitable algorithm should be less sensitive to illumination and more sensitive to growth in order to be able to track significant changes of the ear caused by growth. Methods that are evaluated are the Histogram of Oriented Gradients (HOG), Patterns of Oriented Edge Map (POEM), Local Binary Patterns (LBP) and Gabor Filters. To perform the evaluation, 1000 ear images were generated from 100 ear images, 10 per each subject. For each subject, all 10 images have different illumination and another 10 have different geometrical changes. The results obtained show that a combination of HOG and LBP is suitable for ear recognition under geometrical and illumination changes.

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