基于HOG与改进的SVM的手掌静脉识别算法

手掌静脉识别是一种新兴的生物特征识别技术，随着时代的进步，在各种安全领域中起着越来越重要的影响和应用。提出了一种改进的手掌静脉图像预处理方法，采用对像素灰度值映射来增强图像中的静脉纹理以去除其他干扰。针对手掌静脉纹理的特征提取和识别，提出了一种基于方向梯度直方图（HOG）与改进的阈值支持向量机（T-SVM）的算法，以更好适应手掌静脉识别的特点。通过大量实验证明，该方法不仅可以较为迅速地进行身份识别，而且达到了较高的识别率。

Palm vein recognition algorithm based on HOG and improved SVM

As a new emerging kind of biometrics technology, it plays an increasingly important influence and application in various security fields with the progress of the times. This paper presents an improved palm vein image preprocessing methods, using a pixel gray value mapping to enhance the image of the vein textures to remove other distractions. For palm vein texture feature extraction and recognition, this paper presents a palm vein recognition algorithm based on Histogram of Oriented Gradients（HOG） and improved Threshold Support Vector Machine（T-SVM） to better adapt to the palm vein recognition features. The experimental results demonstrate that the proposed algorithm can not only be more rapid identification and recognition rate but also reach a high accuracy.