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A new retinal image processing method for human identification using radon transform

机译:利用radon变换识别视网膜图像的新方法。

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The blood vessels of retinal image have a unique pattern, from eye to eye and person to person. We have used this trait for designed a new person identification system. This approach focused on blood vessels around the optical disc instead of extracting total retinal blood to optimize the computational cost. At first, optical disc is localized using template matching technique and uses it to rotate the retinal image to reference position. This process compensate the rotation effects which might occur during scanning process then a circular region of interest (ROI) around optical disc is selected. Next, a rotation invariant template is created from each ROI by a polar transformation. In the next stage, vessels from each template are enhanced. Radon transform is used for feature definition in our method. Finally we employ 1D discrete Fourier transform and Euclidian distance for feature matching. The proposed algorithm was tested on a 200 image from DRIVE database [9]. Experimental results on the database demonstrated an average identification rate equal to 100 percent for our identification system.
机译:视网膜图像的血管具有独特的模式,从眼睛到眼睛和人。我们使用这种特性设计了一个新的人识别系统。这种方法集中在光盘周围的血管,而不是提取总视网膜血以优化计算成本。首先,光盘使用模板匹配技术本地化,并使用它将视网膜图像旋转到参考位置。该过程补偿了在扫描过程中可能发生的旋转效果,然后选择光盘周围的圆形感兴趣区域(ROI)。接下来,通过极性转换从每个ROI创建旋转不变模板。在下一阶段,来自每个模板的船舶都得到了增强。 Radon变换用于我们的方法中的特征定义。最后,我们使用1D离散的傅里叶变换和欧几里德距离进行特征匹配。从驱动数据库[9]的200图像上测试了所提出的算法。数据库的实验结果表明,我们的识别系统的平均识别率等于100%。

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