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首页> 美国卫生研究院文献>Computational and Mathematical Methods in Medicine >Finger Vein Segmentation from Infrared Images Based on a Modified Separable Mumford Shah Model and Local Entropy Thresholding
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Finger Vein Segmentation from Infrared Images Based on a Modified Separable Mumford Shah Model and Local Entropy Thresholding

机译：基于改进的可分离Mumford Shah模型和局部熵阈值的红外图像手指​​静脉分割

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摘要

A novel method for finger vein pattern extraction from infrared images is presented. This method involves four steps: preprocessing which performs local normalization of the image intensity, image enhancement, image segmentation, and finally postprocessing for image cleaning. In the image enhancement step, an image which will be both smooth and similar to the original is sought. The enhanced image is obtained by minimizing the objective function of a modified separable Mumford Shah Model. Since, this minimization procedure is computationally intensive for large images, a local application of the Mumford Shah Model in small window neighborhoods is proposed. The finger veins are located in concave nonsmooth regions and, so, in order to distinct them from the other tissue parts, all the differences between the smooth neighborhoods, obtained by the local application of the model, and the corresponding windows of the original image are added. After that, veins in the enhanced image have been sufficiently emphasized. Thus, after image enhancement, an accurate segmentation can be obtained readily by a local entropy thresholding method. Finally, the resulted binary image may suffer from some misclassifications and, so, a postprocessing step is performed in order to extract a robust finger vein pattern.
机译：提出了一种从红外图像提取手指静脉图案的新方法。该方法包括四个步骤：预处理，对图像强度进行局部归一化，图像增强，图像分割，最后进行图像清洁后处理。在图像增强步骤中，寻求既平滑又类似于原始图像的图像。通过最小化修改后的可分离Mumford Shah模型的目标函数来获得增强的图像。由于这种最小化过程对于大图像而言是计算密集型的，因此提出了Mumford Shah模型在小窗口邻域中的本地应用。指静脉位于凹入的非光滑区域，因此，为了将它们与其他组织部分区分开，通过模型的局部应用获得的平滑邻域之间的所有差异以及原始图像的相应窗口均为添加。之后，已经充分强调了增强图像中的静脉。因此，在图像增强之后，可以通过局部熵阈值化方法容易地获得准确的分割。最后，生成的二进制图像可能会遭受一些错误分类，因此，为了提取鲁棒的手指静脉图案，需要执行后处理步骤。

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