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Proceedings Paper

Ear segmentation using histogram based K-means clustering and Hough transformation under CVL dataset
Author(s): Heng Liu; Dekai Liu
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Paper Abstract

Under CVL dataset, we provide an image segmentation approach based on adaptive histogram based K-means clustering and fast Hough transformation. This work firstly analyzes the characteristics of ear images in CVL face dataset. According to the analysis, we then use adaptive histogram based K-means clustering method to threshold ear images and then roughly segment the ear parts. After ear contour extraction, with boundary determination through vertical project, Hough transformation is utilized to locate the ear contour accurately. The experimental results and comparisons with other segmentation methods show our approach is effective.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74952N (30 October 2009); doi: 10.1117/12.832662
Show Author Affiliations
Heng Liu, Southwest Univ. of Science and Technology (China)
Shanghai Jiao Tong Univ. (China)
Dekai Liu, Southwest Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7495:
MIPPR 2009: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Bruce Hirsch; Zhiguo Cao; Hanqing Lu, Editor(s)

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