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Vein Segmentation in Infrared Images Using Compound Enhancing and Crisp Clustering

机译:使用复合增强和清晰聚类的红外图像静脉分割

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摘要

In this paper an efficient fully automatic method for finger vein pattern extraction is presented using the second order local structure of infrared images. In a sequence of processes, the veins structure is normalized and enhanced, eliminating also the fingerprint lines using wavelet decomposition methods. A compound filter which handles the second order local structure and exploits the multidirectional matching filter response in the direction of the smallest curvature is used in order to enrich the vein patterns. Edge suppression decreases the misclassified edges as veins in the forthcoming crisp clustering step. In a postprocessing module, a morphological majority filter is applied in the segmented image to smooth the contours and to remove some small isolated regions and a reconstruction process reduces the outliers in the finger vein pattern. The proposed method was evaluated in a small database of infrared images giving excellent detection accuracy of vein patterns.
机译:本文利用红外图像的二阶局部结构,提出了一种高效的全自动手指静脉纹样提取方法。在一系列过程中,静脉结构被规范化和增强,同时使用小波分解方法消除了指纹线。使用复合滤波器处理二阶局部结构,并在最小曲率方向上利用多方向匹配滤波器响应,以丰富静脉图案。在即将到来的脆性聚类步骤中,边缘抑制将错误分类的边缘减少为静脉。在后处理模块中,将形态学多数过滤器应用于分割后的图像中,以平滑轮廓并去除一些小的孤立区域,并且重建过程可以减少手指静脉图案中的离群值。该方法在红外图像的小型数据库中进行了评估,该数据库具有出色的静脉图样检测准确性。

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