Background: Purely epistatic multi-locus interactions cannot generally be detected via singlelocus analysis in case-control studies of complex diseases. Recently, many two-locus and multilocus analysis techniques have been shown to be promising for the epistasis detection. However, exhaustive multi-locus analysis requires prohibitively large computational efforts when problems involve large-scale or genome-wide data. Furthermore, there is no explicit proof that a combination of multiple two-locus analyses can lead to the correct identification of multi-locus interactions.

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This paper presents counting number of points for the P.acne vulgaris using UV Fluorescence and image processing. This proposed method uses a process of image processing as follows. Cropping a UV image is to select a region of interest and, then the cropped image is resized for a suitable size and it (or the color image) is converted to a gray image. Quality of this gray image will be improved for image enhancement using adaptive histogram equalization. Finally, extended maxima transform, i.e. the regional maxima of the H-maxima transform, is used for counting number of the P.acne points. The experimental results show that the accuracy, sensitivity and precision are approximately at 83.75%, 98.22% and 85.04%, respectively. It saves time to analysis of the acne points.