Abstract
Retinal blood vessel detection is a fundamental procedure for automatic detection of retinal diseases and infections. This paper presents a method for blood vessel detection of retinal images using adaptive histogram equalization and morphological operations. After proper intensity adjustments, the image is subjected to morphological operations and then passed through a median filter. Threshold of the filtered image is then carried out to give a resultant image. The final image is obtained using vessel width dependent morphological filters to remove all the connected components that have fewer than the required pixel width; i.e., all the small components are removed. The performance of the proposed is very promising as compared to the existing techniques.
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Halder, A., Sarkar, A., Ghose, S. (2019). Adaptive Histogram Equalization and Opening Operation-Based Blood Vessel Extraction. In: Nayak, J., Abraham, A., Krishna, B., Chandra Sekhar, G., Das, A. (eds) Soft Computing in Data Analytics . Advances in Intelligent Systems and Computing, vol 758. Springer, Singapore. https://doi.org/10.1007/978-981-13-0514-6_54
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DOI: https://doi.org/10.1007/978-981-13-0514-6_54
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