【摘要】 针对手背静脉识别过程中采集的图像出现干扰信息的问题,提出了一种基于有效维度特征的识别算法。首先,该算法对采集的图像进行自适应中值滤波去噪;其次,对图像进行分块处理,并基于混合高斯模型与梯度信息对子图像提取特征;然后,依据子图像间特征相似性,提出了判断子图像是否为干扰信息的方法;最后,融合所有真实静脉区域的特征,形成特征向量,并采用基于稀疏表示的算法对多种有效维度下的特征向量进行匹配。实验表明,该算法具有较高的准确识别率,即使采集的手背静脉图像存在部分遮挡,算法依然能够获得较好的识别效果。更多还原

【Abstract】 During dorsal vein recognition processing,for the problem that there may be some distractive information in acquired image,a recognition algorithm based on effective dimensional feature was proposed.Firstly,adaptive median filtering algorithm is applied in acquired image for denoising.Secondly,image is divided into blocks,and every sub image feature is extracted based on Gaussian mixture model and gradient information.Then,according to feature similarity between sub images,the method which judges whether the sub image includes distractive information or not is proposed.Finally,vein image feature vector can be acquired through fusing the characteristics of all sub images with real vein information,and sparse representation algorithm is proposed to match the feature vector of unknown sample with different effective dimensions.Experiments show that high recognition rate can be achieved by the proposed algorithm,and even though part of the region in vein image is blocked,good recognition effect can be also acquired.更多还原