首页> 外文期刊>International Journal of Electrical and Computer Engineering >Retinal Blood Vessels Extraction Based on Curvelet Transform and by Combining Bothat and Tophat Morphology
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Retinal Blood Vessels Extraction Based on Curvelet Transform and by Combining Bothat and Tophat Morphology

机译:基于Curvelet变换和Topat和Tophat形态相结合的视网膜血管提取

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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.
机译:视网膜图像包含有关视觉系统感觉部分健康的重要信息。提取这些特征是针对医学或人类识别的各种应用分析视网膜图像的第一步,也是最重要的一步。所提出的方法包括预处理,对比增强和血管提取阶段。在预处理中,由于来自彩色视网膜图像的绿色通道在子带之间具有最高的对比度,因此选择了绿色分量。为了使图像的亮度均匀,使用了自适应直方图均衡化,因为它为图像提供了均匀的,较暗的背景和较亮的血管灰度。此外,Curvelet变换用于通过以各种比例和方向突出显示图像的边缘来增强图像的对比度。最终提供了Bothat和Tophat形态功能的组合,然后进行局部阈值化以对血管进行分类。因此,视网膜血管与背景图像分离。

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