TY  - CONF
AV  - none
N1  - cited By 8; Conference of 3rd National Postgraduate Conference - Energy and Sustainability: Exploring the Innovative Minds, NPC 2011 ; Conference Date: 19 September 2011 Through 20 September 2011; Conference Code:88531
Y1  - 2011///
TI  - Identification of acne lesions, scars and normal skin for acne vulgaris cases
KW  - acne lesions; Acne vulgaris; CIELAB color; Color space; Computational imaging; Euclidean distance; Flash photography; Manual methods; Medical Image Processing; Normal skin; Segmentation results; Sensitivity and specificity; Visual assessments
KW  -  Color photography; Image processing; Image segmentation; Sustainable development
KW  -  Dermatology
A1  - Ramli, R.
A1  - Malik, A.S.
A1  - Hani, A.F.M.
A1  - Yap, F.B.-B.
SN  - 9781457718847
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857074377&doi=10.1109%2fNatPC.2011.6136340&partnerID=40&md5=3512271908f6028b2693d2d9f44effc1
CY  - Perak
N2  - Acne affects 85 of adolescents at some time during their lives. There are various causes for acne including genetic, hormonal, sebaceous activity, bacteria, climate, chemical and psychological. Till now, dermatologists use manual methods such as direct visual assessment and ordinary flash photography to assess the acne. These methods are very time consuming and tedious. To address these issues, researchers in recent years have proposed computational imaging methods for aiding in the acne diagnosis. This paper proposes an algorithm to identify acne lesions, scars and normal skin features from photographs taken by Digital Single-Lens Reflex (DSLR) cameras. The images are converted from RGB to CIELAB color space, thresholded to three clusters and segmented using minimum Euclidean distance. The segmentation results from randomly selected images show sensitivity and specificity of greater than 80. © 2011 IEEE.
ID  - scholars1686
ER  -