Automatic detection of acne scars: Preliminary results

Biman Chandra Dey, B. Nirmal, Ramesh R. Galigekere

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (SciVal)


Acne scars are of great cosmetic concern, and there are several methods of treatment towards reducing the appearance of scars. Automatic detection of acne scar-pixels from digital color images would be helpful in quantitative assessment of the success of treatment. This paper addresses detection of acne scar-pixels based on color image processing. The RGB model is used to representing the data. Pixels from the background (skin) and from the lesions of interest (acne scars) were recorded from the images of 7 subjects, to build a knowledge-base i.e., clusters associated with the skin and acne scars, respectively. The clusters were found to be fairly distinct in the RGB space. Consequently, classification (segmentation) is performed by minimum-distance- rule in the RGB space, by using Mahalanobis distance (MD). We have also implemented Bayes' method. The results have been validated with respect to the ground-truth extracted by manual segmentation of scars. The classifier based on MD performs better than that based on Bayes, with the average values of sensitivity and specificity of the former being 90.36 and 93.82, respectively.

Original languageEnglish
Title of host publicationIEEE EMBS Special Topic Conference on Point-of-Care (POC) Healthcare Technologies
Subtitle of host publicationSynergy Towards Better Global Healthcare, PHT 2013
Number of pages4
Publication statusPublished - 08-03-2013
Event1st IEEE-EMBS Conference on Point-of-Care Healthcare Technologies, PHT 2013 - Bangalore, India
Duration: 16-01-201318-01-2013


Conference1st IEEE-EMBS Conference on Point-of-Care Healthcare Technologies, PHT 2013

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


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