Abstract
Diabetics is the common disease faced by many of the people in India. It can be detected through microaneurysm. Using genetic algorithm and SVM classification techniques, sores are viewed as the most punctual indications of diabetic retinopathy. The diabetic retinopathy is an infection caused by diabetes and is considered as the significant reason for visual impairment in working age populace. The proposed technique depends on numerical morphology and comprises in expelling parts of retinal life systems to achieve the sores. This strategy comprises of four phases: (a) Image acquisition; (b) Preprocessing; (c) Extracting the features using genetic algorithm; (d) Classification. The exactness of the strategy was obtained using genetic algorithm and SVM classifier is also applied to identify whether the person is diabetic or non diabetic patient.
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Gnaneswara Rao, N., Deva Kumar, S., Sravani, T., Ramakrishnaiah, N., Rama Krishna S, V. (2019). Microaneurysm Detection in Diabetic Retinopathy Using Genetic Algorithm and SVM Classification Techniques. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1036. Springer, Singapore. https://doi.org/10.1007/978-981-13-9184-2_25
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DOI: https://doi.org/10.1007/978-981-13-9184-2_25
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