期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2014
卷号：4
期号：3
页码：389-397
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Retinal image contains vital information about the health of the sensory part of the visual system. Extracting these features is the first and most important step to analysis of retinal images for various applications of medical or human recognition. The proposed method consists of preprocessing, contrast enhancement and blood vessels extraction stages. In preprocessing, since the green channel from the coloured retinal images has the highest contrast between the subbands so the green component is selected. To uniform the brightness of image adaptive histogram equalization is used since it provides an image with a uniformed, darker background and brighter grey level of the blood vessels. Furthermore Curvelet transforms is used to enhance the contrast of an image by highlighting its edges in various scales and directions. Eventually the combination of Bothat and Tophat morpholological function followed by local thresholding is provided to classify the blood vessels. Hence the retinal blood vessels are separated from the background image. DOI: http://dx.doi.org/10.11591/ijece.v4i3.6327
其他摘要：Retinal image contains vital information about the health of the sensory part of the visual system. Extracting these features is the first and most important step to analysis of retinal images for various applications of medical or human recognition. The proposed method consists of preprocessing, contrast enhancement and blood vessels extraction stages. In preprocessing, since the green channel from the coloured retinal images has the highest contrast between the subbands so the green component is selected. To uniform the brightness of image adaptive histogram equalization is used since it provides an image with a uniformed, darker background and brighter grey level of the blood vessels. Furthermore Curvelet transforms is used to enhance the contrast of an image by highlighting its edges in various scales and directions. Eventually the combination of Bothat and Tophat morpholological function followed by local thresholding is provided to classify the blood vessels. Hence the retinal blood vessels are separated from the background image. DOI: http://dx.doi.org/10.11591/ijece.v4i3.6327
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