This repository gathers three basic image processing implementation in MATLAB to detect face acne. These methods were implemented from available literature. In addition, it poses a method (severity.m) to evaluate severity based on the acne quantity. This severity is classified into 'Mild', 'Moderate', 'Severe' and 'Very Severe', its criteria were taken from the paper:
HAYASHI, Nobukazu, et al. Establishment of grading criteria for acne severity.
The Journal of dermatology, 2008, vol. 35, no 5, p. 255-260.
The first method is in the file min2012.m and was implemented from the paper:
MIN, Seonguk, et al. Development and evaluation of an automatic acne lesion detection program
using digital image processing. Skin Research and Technology, 2013, vol. 19, no 1, p. e423-e432.
The second method is in file Thanapa.m and was implemented from the paper:
CHANTHARAPHAICHI, Thanapha, et al. Automatic acne detection for medical treatment.
En 2015 6th International Conference of Information and Communication Technology
for Embedded Systems (IC-ICTES). IEEE, 2015. p. 1-6.
The third method is in the file KmeansAcneSegmentation.m and uses k-means for color segmentation. It was implemented from different references.
The image example used is acne-face-1-10.jpg It is an example taken from the images examples in the dataset https://dermnetnz.org/
The following images show the output of each method.
David Castro Piñol. (2020, February 16). Dacapi91/AcneDetectionAssessment: AcneDetection (Version v1.1). Zenodo. http://doi.org/10.5281/zenodo.3669021
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Copyright (c) 2020 David Castro Piñol
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