Texture Features Extraction of Human Leather Ports Based on Histogram

  • Sinaga A
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Abstract

Skin problems general are distinguished on healthy and unhealthy skin. Based on the pores, unhealthy skin: dry, moist or oily skin. Skin problems are identified from the image capture results. Skin image is processed using histogram method which aim to get skin type pattern. The study used 7 images classified by skin type, determined histogram, then extracted with features of average intensity, contrast, slope, energy, entropy and subtlety. Specified skin type reference as a skin test comparator. The histogram-based skin feature feature aims to determine the pattern of pore classification of human skin. The results of the 1, 2, 3 leaf image testing were lean to normal skin (43%), 4, 5, tends to dry skin (29%), 6.7 tend to oily skin (29%). Percentage of feature-based extraction of histogram in image processing reaches 90-95%.

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APA

Sinaga, A. S. (2018). Texture Features Extraction of Human Leather Ports Based on Histogram. Indonesian Journal of Artificial Intelligence and Data Mining, 1(2), 92. https://doi.org/10.24014/ijaidm.v1i2.6084

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