针对局部方向模式(LDP)识别掌脉时速度慢的问题，提出一种基于改进LDP 的掌脉识别方法。该方法在保留LDP算法原有的Kirsch 模板基础上，直接按照八方向边缘响应符号进行编码，避开排序，减少特征提取时间，即快速局部方向模式(FLDP)。在香港理工大学掌脉图库和自建图库上实验，将掌脉图像分成若干均匀子块，利用FLDP 算法提取各子块的特征向量，融合得到总的模式特征，利用卡方距离进行匹配识别。在两个图库上的实验结果表明，该算法的执行时间分别为17.75 ms 和19.98 ms，优于其他典型算法，同时正确识别率可达到99.8916%和99.3665%，具有应用价值。

For the problem that the feature extraction speed of palm vein recognition mothed based on local directional pattern (LDP) is slowly, a palm vein recognition method based on improved LDP is proposed. On the basis of keeping the Kirsch template of original LDP algorithm, the proposed method can code the edge response symbols in eight directions directly, which avoids sorting and reduces the time of feature extraction. It is called fast local directional pattern (FLDP). The proposed approach is tested on the palm vein datebases of Hong Kong Polytechnic University and the self-built palm vein datebases, the palm vein image is divided into some distributed blocks evenly, where the feature vectors of each sub block are obtained by FLDP algorithm and then the total characteristic fusion model is obtained, the chi-square distance is used for matching identification. Experimental results show that the proposed algorithm execution time is 17.75 ms and 19.98 ms respectively, whose performance obviously surpasses other typical algorithms, at the same time, the recognition rate can reach 99.8916% and 99.3665% . The proposed method has practical application value.