Ear segmentation using histogram based K-means clustering and Hough transformation under CVL dataset

Heng Liu; Dekai Liu

doi:10.1117/12.832662

30 October 2009 Ear segmentation using histogram based K-means clustering and Hough transformation under CVL dataset

Heng Liu, Dekai Liu

Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74952N (2009) https://doi.org/10.1117/12.832662
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

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.

Citation Download Citation

Heng Liu and Dekai Liu "Ear segmentation using histogram based K-means clustering and Hough transformation under CVL dataset", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74952N (30 October 2009); https://doi.org/10.1117/12.832662

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