<![CDATA[Changes in retinal blood vessels feature a sign of serious illnesses such as heart disease and stroke. Therefore, the analysis of retinal vascular features can help in detecting these changes and allow patients to take preventive measures at an early stage of this disease. Automation of this process will help reduce the costs associated with the specialist and eliminate inconsistencies that occur in manual detection system. Among the retinal image analysis, image extraction retinal blood vessels is a crucial step before measurement. In this paper, we use an effective method of automatically extracting the blood vessels of the color images of the retina using a length detector line in several different scales, in order to maintain the strength and eliminates the weaknesses of each detector individual lines, the result of the detection lines on various scales combined to produce a segmentation of each image of the retina. The performance of the method is evaluated quantitatively using DRIVE dataset. Test results show that this method achieve high accuracy is 0.9407 approaching measurement results manually by experts, and this method produces accurate segmentation in detecting retinal blood vessels with effciency by quickly segmenting time is 2.5 seconds per image.]]>
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