TY - GEN
T1 - Accurate wrinkle representation scheme for skin age estimation
AU - Choi, Young Hwan
AU - Tak, Yoon Sik
AU - Rho, Seungmin
AU - Hwang, Eenjun
PY - 2011
Y1 - 2011
N2 - Among many features that can be observed from human skin, wrinkles are known to be very effective for assessing a subject's physical condition, surroundings, or lifestyle. In our previous work, we showed how to extract various wrinkle-related features such as total length, average width, depth, and size from magnified skin images and use them to estimate the degree of skin aging. To represent wrinkles on the skin images, we used a watershed algorithm and constructed its skeleton image, in which wrinkles are represented by 1-pixel lines. A skeleton image consists of polygons, which we call wrinkle cells. Since most wrinkle-related features are deduced from this skeleton image, accurate wrinkle representation is very critical. However, we found that the watershed algorithm produces over-segmentation for skin images; i.e., one wrinkle is represented by multiple smaller wrinkles in the skeleton image. To solve this problem, in this paper we propose an accurate skin wrinkle representation scheme that identifies and merges over-segmented cells in the skeleton image. Various experiments on our prototype system show that our scheme provides accurate skin wrinkle representation and thus improves the accuracy of skin age estimation.
AB - Among many features that can be observed from human skin, wrinkles are known to be very effective for assessing a subject's physical condition, surroundings, or lifestyle. In our previous work, we showed how to extract various wrinkle-related features such as total length, average width, depth, and size from magnified skin images and use them to estimate the degree of skin aging. To represent wrinkles on the skin images, we used a watershed algorithm and constructed its skeleton image, in which wrinkles are represented by 1-pixel lines. A skeleton image consists of polygons, which we call wrinkle cells. Since most wrinkle-related features are deduced from this skeleton image, accurate wrinkle representation is very critical. However, we found that the watershed algorithm produces over-segmentation for skin images; i.e., one wrinkle is represented by multiple smaller wrinkles in the skeleton image. To solve this problem, in this paper we propose an accurate skin wrinkle representation scheme that identifies and merges over-segmented cells in the skeleton image. Various experiments on our prototype system show that our scheme provides accurate skin wrinkle representation and thus improves the accuracy of skin age estimation.
KW - Image processing
KW - Pattern recognition
KW - SVM classifier
KW - Skin age
KW - Watershed algorithm
KW - Wrinkle feature
UR - http://www.scopus.com/inward/record.url?scp=80052574207&partnerID=8YFLogxK
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U2 - 10.1109/MUE.2011.48
DO - 10.1109/MUE.2011.48
M3 - Conference contribution
AN - SCOPUS:80052574207
SN - 9780769544700
T3 - Proceedings of the 2011 5th FTRA International Conference on Multimedia and Ubiquitous Engineering, MUE 2011
SP - 226
EP - 231
BT - Proceedings of the 2011 5th FTRA International Conference on Multimedia and Ubiquitous Engineering, MUE 2011
T2 - 2011 5th FTRA International Conference on Multimedia and Ubiquitous Engineering, MUE 2011
Y2 - 28 June 2011 through 30 June 2011
ER -