基于编码的特征表达方法在光照不变性、运算效率、特征表述能力等方面具有较大优势, 成为新型的特征提取方法之一。手指静脉图像采用红外光透射成像, 加之手指内部其他组织的固有影响, 图像质量普遍较低。将Gabor滤波对图像纹理的增强与局部图结构编码的思想相结合, 重点研究一种新的对称邻域交叉图结构, 将局部邻域的纹理变化转换为加权的编码串。通过不同方向特征编码提取每个通道Gabor滤波图像的特征编码图, 充分表达像素点周围邻域的位置信息和梯度信息, 具有良好的旋转不变性。实验结果表明: 提出的手指静脉特征编码新方法比多种常用特征编码方法具有更好的识别性能, 对图像姿态变化更鲁棒。

The feature representing method based on encoding has advantages in illumination invariance, calculation efficiency and feature representation. It is one of the new feature extracting methods. The finger-vein images were captured in a perspective view by using infrared light source. Due to the complex biological tissue and the imaging mode, the image quality was usually poor. The Gabor filtering was used to enhance the image texture and the local graph structure encoding was adopted. A new feature encoding method was proposed with emphasis on a new local graph structure which was symmetric and crossed in neighborhood. The image texture of local neighborhood was converted to weighted encoding strings. The filtered image of each channel of Gabor filter was encoded in different directions so as to express the information of position and gradient in the neighborhood adequately, and it was rotation invariant as a result. The experiments results show that new method achieves better performance in finger recognition than common feature encoding methods and is more robust in rotation.