非接触指纹图像识别算法研究

发布时间：2018-05-19 23:03

本文选题：非接触指纹 + 高频强调滤波　；参考：《电子学报》2017年11期

【摘要】：非接触指纹识别具有接受程度高、防伪性高、卫生性高等优点,是目前生物特征识别领域的研究热点,但是非接触指纹图像的背景区域比接触式的相对复杂,指纹图像会出现旋转和平移现象,且脊、谷线的对比度较低,这些因素严重影响了非接触指纹的识别性能.采用接触式指纹图像处理方法很难达到良好的处理效果.本文根据非接触指纹图像的特点提出了相应的非接触指纹图像的预处理方法.首先采用图像YCb Cr模型中的Cb分量和Otsu法相结合的方法进行手指区域的提取.其次采用高频强调滤波和迭代自适应直方图均衡化相结合的图像增强算法进行图像增强处理,再用简化的Gabor函数模板进行二次增强,然后提出了一种手指指纹ROI区域提取的方法.最后本文采用基于AR-LBP算法进行特征提取,利用最近邻分类器进行特征匹配.实验结果表明,本文提出的非接触指纹算法能够达到很好的图像识别效果.
[Abstract]:Non-contact fingerprint recognition has many advantages, such as high acceptance, high anti-counterfeiting, high sanitation, etc., it is a hotspot in biometric identification field, but the background area of non-contact fingerprint image is more complex than that of contact fingerprint image. The rotation and translation of fingerprint images and the low contrast between ridges and valleys seriously affect the recognition performance of non-contact fingerprints. Contact fingerprint image processing method is difficult to achieve good processing results. According to the characteristics of the contactless fingerprint image, this paper presents the corresponding preprocessing method of the contactless fingerprint image. Firstly, the method of combining the CB component in the image YCb Cr model with the Otsu method is used to extract the finger region. Secondly, the image enhancement algorithm combined with high-frequency emphasis filter and iterative adaptive histogram equalization is used to enhance the image, and then the simplified Gabor function template is used for secondary enhancement. Then a method to extract ROI region from finger fingerprint is proposed. Finally, feature extraction based on AR-LBP algorithm and feature matching based on nearest neighbor classifier are used in this paper. Experimental results show that the contactless fingerprint algorithm proposed in this paper can achieve a good image recognition effect.
【作者单位】：哈尔滨工程大学自动化学院;
【基金】：国家自然科学基金面上项目(No.61573114) 黑龙江省自然科学基金面上项目(No.F2015033) 中央高校基本科研基金(No.HEUCFJ170404)
【分类号】：TP391.41

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