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All Journal Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK)
Siti Sarah Abdullah
Universitas Suryakancana
Computer Science & IT Economics, Econometrics & Finance Social Sciences Other

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Deteksi Penyakit Mata Merah Menggunakan Histogram Oriented Gradient dan Support Vector Machine Siti Sarah Abdullah; Syamsy Wiguna Putra Dwi Raksa
Prosiding Vol 4 (2022): SNISTEK
Publisher : LPPM Universitas Putera Batam

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Abstract

The health sector has adopted Information Technology to help medical expert work easier, include ophthalmologists. An Ophthalmologists diagnoses red eyes with test series to determine diseases of the eye. It takes time and accuracy. Further searching, it turns out that red eyes have a pattern that indicates a certain disease. The research idea is to identify red eye patterns, which is done by identifying patterns in red eye disesase using the Histogram Oriented Gradient (HOG). As a sample, two cases of red eye disease were taken: conjunctival injection and ciliary injection. First step is preprocessing stage, which is specifying the image according to the needs, then converting the colored object to grayscale, then croped and resized it. Next step is calculated gradient of pixels. Result of the resaeGradients resulted classified using Support Vector Machine. The result obtained from the study, could be detected conjunctival injection and ciliary injection based on classification
Co-Authors Syamsy Wiguna Putra Dwi Raksa