Ear feature region detection based on a combined image segmentation algorithm-KRM

Jingying Jiang; Hao Zhang; Qi Zhang; Junsheng Lu; Zhenhe Ma; Kexin Xu

doi:10.1117/12.2036893

26 February 2014 Ear feature region detection based on a combined image segmentation algorithm-KRM

Jingying Jiang, Hao Zhang, Qi Zhang, Junsheng Lu, Zhenhe Ma, Kexin Xu

Proceedings Volume 8942, Dynamics and Fluctuations in Biomedical Photonics XI; 89420Z (2014) https://doi.org/10.1117/12.2036893
Event: SPIE BiOS, 2014, San Francisco, California, United States

Abstract

Scale Invariant Feature Transform（SIFT）algorithm is widely used for ear feature matching and recognition. However, the application of the algorithm is usually interfered by the non-target areas within the whole image, and the interference would then affect the matching and recognition of ear features. To solve this problem, a combined image segmentation algorithm i.e. KRM was introduced in this paper, As the human ear recognition pretreatment method. Firstly, the target areas of ears were extracted by the KRM algorithm and then SIFT algorithm could be applied to the detection and matching of features. The present KRM algorithm follows three steps: (1)the image was preliminarily segmented into foreground target area and background area by using K-means clustering algorithm; (2)Region growing method was used to merge the over-segmented areas; (3)Morphology erosion filtering method was applied to obtain the final segmented regions. The experiment results showed that the KRM method could effectively improve the accuracy and robustness of ear feature matching and recognition based on SIFT algorithm.

Citation Download Citation

Jingying Jiang, Hao Zhang, Qi Zhang, Junsheng Lu, Zhenhe Ma, and Kexin Xu "Ear feature region detection based on a combined image segmentation algorithm-KRM", Proc. SPIE 8942, Dynamics and Fluctuations in Biomedical Photonics XI, 89420Z (26 February 2014); https://doi.org/10.1117/12.2036893

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available