Abstract
Automatic detection of the retinal blood vessel can be used in biometric identification, computer assisted laser surgery, and diagnosis of many eye related diseases. Early detection of retinal blood vessel helps people to take proper treatment against diseases such as diabetic retinopathy, hypertension which can significantly reduce possible vision loss. This paper presents an efficient and simple contrast enhancement technique where morphological operations like top-hat and bottom-hat are applied to enhance the image. Edge Content-based contrast matrix is measured for selecting the optimal structuring element size and simple straightforward steps are applied for completely extracting the vessels from the enhanced retinal image. The proposed method acquires an average accuracy rate of 0.9379 and 0.9504 on two publicly available DRIVE and STARE benchmark dataset respectively.
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Kushol, R., Kabir, M.H., Salekin, M.S., Rahman, A.B.M.A. (2017). Contrast Enhancement by Top-Hat and Bottom-Hat Transform with Optimal Structuring Element: Application to Retinal Vessel Segmentation. In: Karray, F., Campilho, A., Cheriet, F. (eds) Image Analysis and Recognition. ICIAR 2017. Lecture Notes in Computer Science(), vol 10317. Springer, Cham. https://doi.org/10.1007/978-3-319-59876-5_59
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DOI: https://doi.org/10.1007/978-3-319-59876-5_59
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