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Acne Segmentation and Classification using Region Growing and Self-Organizing Map

Satiabudhi, Gregorius and Adipranata, Rudy and Gunawan, Ari (2017) Acne Segmentation and Classification using Region Growing and Self-Organizing Map. [UNSPECIFIED]

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    Abstract

    Acne vulgaris is a common skin disease found in human of all ages and genders. Acnes have different types according to their severity. In this research, an application was developed to segment and process the classification an acne object in humans face. The process begins with the insertion of several seed points on a picture. Each of those seed points were developed further into a region that mask the whole acne using region growing method. Afterward, the regions were grouped together with other acne of similar features using self-organizing map. According to the experimental result, the region growing method gives a satisfying result to do segmentation on an acne object. But it should be pointed out that every different acne object requires different threshold to achieve an ideal result. Self-organizing map gives an undesirable result, as the input picture with different skin colors and lighting conditions affect the accuracy of the result.

    Item Type: UNSPECIFIED
    Uncontrolled Keywords: acne segmentation, acne classification, region growing, self-organizing map
    Subjects: Q Science > QA Mathematics > QA76 Computer software
    Divisions: Faculty of Industrial Technology > Informatics Engineering Department
    Depositing User: Admin
    Date Deposited: 11 Jul 2018 16:21
    Last Modified: 24 Jul 2018 20:47
    URI: http://repository.petra.ac.id/id/eprint/17867

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