DocumentCode :
172679
Title :
Selective quantifiable facial assessment of aging
Author :
Mehta, Garima ; Druzgalski, C.
Author_Institution :
Dept. of Electr. Eng., California State Univ. - Long Beach, Long Beach, CA, USA
fYear :
2014
fDate :
7-12 April 2014
Firstpage :
1
Lastpage :
6
Abstract :
Imaging represents a technique of choice in evaluation of the visual effects of aging and associated with that occurrence of wrinkles. In particular, skin wrinkles typically occur due to aging processes, including loss of body mass, sun damage, smoking, squinting and other factors. They represent a clear and easily accessible indicator of changes. As such, one can also acquire useful information about the aging process in skin by analyzing the wrinkles. To this end, we utilize a combination of numerical techniques, including color quantization, image segmentation, and various edge detection algorithms in order to perform automated wrinkle counting and wrinkle density calculations. As a more appropriate alternative to chronological age, such a methodology allows us to come up with quantifiable measures for skin aging, which may be used for performing statistics and extracting general patterns associated with physiological aging of the skin, as well as extending such numerical techniques for other biomedical applications in which distinct topological features contain important information about biological processes. Different subjects were used to test the techniques and extract aging patterns by examining the skin immediately underneath the lower eyelid as our region of interest. Numerically processed photographs, included counting the number of wrinkles meeting predefined threshold conditions, and calculating the corresponding wrinkle density for a given subject and particular conditions. Applicability and practicality of different edge detection methods were also a part of the studies as demonstrated.
Keywords :
biomedical optical imaging; edge detection; feature extraction; image colour analysis; image segmentation; medical image processing; numerical analysis; skin; biomedical applications; chronological age; color quantization; edge detection algorithms; edge detection methods; facial assessment; image segmentation; numerical techniques; pattern extraction; photographs; skin aging; skin wrinkle counting; skin wrinkle density calculations; statistics; topological features; visual effect evaluation; Aging; Cameras; Gray-scale; Image color analysis; Image edge detection; Physiology; Skin; Skin wrinkles; edge detection; numerical analysis; skin aging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Health Care Exchanges (PAHCE), 2014 Pan American
Conference_Location :
Brasilia
ISSN :
2327-8161
Print_ISBN :
978-1-4799-3554-3
Type :
conf
DOI :
10.1109/PAHCE.2014.6849637
Filename :
6849637
Link To Document :
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