학술논문

Implementation of Linear Structuring Element in OpenCV for Blood Vessel Segmentation from Color Fundus Images
Document Type
Conference
Source
2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT) Computing, Communication and Networking Technologies (ICCCNT), 2019 10th International Conference on. :1-5 Jul, 2019
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Blood vessels
Biomedical imaging
Retina
Image segmentation
Image color analysis
Morphology
Image reconstruction
Blood vessel
Mathematical morphology
fundus image
linear structuring element
Language
Abstract
This paper presents an improved blood vessel segmentation technique from color fundus images using morphology operation. More accurate blood vessel segmentation from fundus images plays key role for screening of diabetic retinopathy and glaucoma. This paper has made significant contributions by developing linear structuring element for blood vessel detection using OpenCV. The proposed method involves three stages namely; pre-processing, generation of linear structuring element and detection of blood vessels from fundus image, In first stage, color fundus images are pre-processed or enhanced as these images often suffer from uneven illumination, low contrast and noise. In second stage, twelve linear structuring elements are generated and finally, in the third stage, blood vessel segmentation algorithm is applied to improve the extraction of diagnostic features such as microaneurysms and hemorrhages, leading to more accurate detection of diabetic retinopathy.