基于感兴趣区域函数优化的静脉图像分割算法

提出一种基于局部感兴趣区域中熵与梯度函数优化的近红外手背静脉图像分割算法。该算法首先基于压缩感知理论对图像进行去噪。其次，通过条带波变换提取存在静脉信息的感兴趣区域，在这些区域中对建立的关于熵和梯度的函数进行约束与优化，实现静脉与背景分离。最后，融合所有区域的分割结果，完成静脉图像的分割。实验表明在处理近红外静脉图像分割问题时，该算法相对其它算法能保留更完整的静脉特征。此外，该算法对于具有纹理特征的指静脉、掌静脉图像的分割具有较好的借鉴价值。

Vein Image Segmentation Algorithm Based on Function Optimization in Regions of Interest

A near infrared dorsal hand vein image segmentation algorithm is proposed based on function optimization about entropy and gradient in local regions of interest. The noise is removed by applying compressed sensing theory in vein image firstly. Then,the Bandelet transform is used to extract the regions of interest including vein information,and the established function about entropy and gradient is constrained and optimized in these regions so that the vein information and the background can be separated. Finally,the segmentation results in all the regions of interest are fused,and the whole vein image segmentation process is accomplished. The experimental results show that the proposed algorithm makes the acquired segmentation image reserve better vein features than other segmentation algorithms. In addition,the proposed algorithm has good reference value in the segmentation of finger vein and palm vein images with texture features.