Deteksi Penyakit Mata Merah Menggunakan Histogram Oriented Gradient dan Support Vector Machine
Keywords:Red eye disease, Histogram Oriented Gradient, Support Vector Machine
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
Alamsyah, D. (2017). Pengenalan Mobil pada Citra Digital Menggunakan HOG-SVM. JATISI.
Campbell, C., & Ying, Y. (2011). Learning with Support Vector Machines. Morgan & Claypool Publishers.
Dalal, N., & Triggs, B. (2005). Histograms of Oriented Gradients for Human Detection. Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 886-893.
Mallick, S. (2016, December 6). Histogram of Oriented Gradients explained using OpenCV. Retrieved from LearnOpenCV: https://learnopencv.com/histogram-of-oriented-gradients/
Yulianti, S., & Ilyas, S. (2015). Ilmu Penyakit Mata Edisi kelima. Jakarta: Kedokteran Universitas Indonesia.
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