基于可控方向值方图算法的掌纹图像特征提取技术

Palmprint Image Feature Extraction Technology Based on Controllable Direction Value Square Diagram Algorithm

采用多通滤波检测器实现对掌纹图像的特征信息采集,对采集的掌纹图像进行不同层次的特征信息分割,通过深层特征提取方法实现对掌纹图像特征融合处理。构建掌纹图像的可控方向值二维融合调度模型,结合多维多视角图像的分割先验知识,建立掌纹图像特征提取的可控方向值方图;分析掌纹图像的浅层特征信息和深层特征信息,对各层特征信息实现信息融合;利用可控方向值方图融合算法实现对掌纹图像特征提取和识别优化。仿真结果表明,采用该方法进行掌纹图像特征提取的精度较高、误分率较小,提高了对掌纹图像的识别和检测能力。

The feature information of palmprint image is collected by multi-pass filter detector and the feature information of palmprint image is segmented at different levels.The feature fusion of palmprint image is realized by deep feature extraction method.A two dimensional fusion scheduling model of the controllable direction values of palmprint images is constructed,and a square of the controllable direction values for feature extraction of palmprint images is established by combining the prior knowledge of multi-dimensional image segmentation from multiple perspectives.The shallow feature information and deep feature information of palmprint image are analyzed to realize information fusion of each layer feature information.The feature extraction and recognition optimization of palmprint image are realized by using the controllable direction value square image fusion algorithm.The simulation results show that the accuracy of palmprint feature extraction with this method is higher,the error rate is lower,and the recognition and detection ability of palmprint image is improved.