Özet:

Abstract One facial skin problem is redness. On site examination currently relies on examination through direct observations conducted by doctors and the patient's medical history. However, some patients are reluctant to consult with a doctor because of shame or prohibitive costs. This study attempts to utilize digital image processing algorithms to analyze the patient's facial skin condition automatically, especially redness detection in the face image. The method used for detecting red objects on face skin for this research is Redness method. The output of the Redness method will be optimized by feature selection based on area, mean intensity of the RGB color space, and mean intensity of the Hue Intensity. The dataset used in this research consists of 35 facial images. The sensitivity, specificity, and accuracy are used to measure the detection performance. The performance achieved 54%, 99.1%, and 96.2% for sensitivity, specificity, and accuracy, respectively, according to dermatologists. Meanwhile, according to PT. AVO personnel, the performance achieved 67.4%, 99.1%, and 97.7%, for sensitivity, specificity, and accuracy, respectively. Based on the result, the system is good enough to detect redness in facial images.

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