改进MOSSE的小面积滑动指纹图像追踪算法

Improved MOSSE small area sliding fingerprint image tracking algorithm

随着指纹传感器采集的指纹图像趋向于小型化,指纹图像所包含的指纹特征信息越来越少。针对传统模板匹配算法在处理小面积滑动指纹时计算量大、精度不理想、抗干扰能力差等问题,本文提出一种基于MOSSE的改进滑动指纹追踪算法。改进MOSSE算法使用多输入,将灰度特征与HOG特征在响应层加权融合,并引入Fourier-Mellin算法、加汉宁窗用以处理发生旋转的指纹。通过多种算法对小面积指纹进行跟踪的结果进行对比,表明本算法继承了原MOSSE算法的优点,并提高了指纹匹配精度,对正常图像匹配精度为99%,对含噪声图像匹配精度为90.3%,每帧均值计算时间为0.1036 s,保证了指纹追踪的实时性,鲁棒性强,对产生形变和旋转的指纹图像也能进行很好的跟踪。

As the fingerprint image collected by the fingerprint sensor tends to become miniaturized,the fingerprint image contains less and less fingerprint feature information.Aiming at the problems of large calculation,unsatisfactory accuracy and poor anti-interference ability of traditional template matching algorithms when processing small-area sliding fingerprints,this paper proposes an improved sliding fingerprint tracking algorithm based on MOSSE.The improved MOSSE algorithm uses multiple inputs,weighted fusion of grayscale features and HOG features at the response layer,and introduces the Fourier-Mellin algorithm and Hanning window to process the fingerprint of rotation.The results of tracking small-area fingerprints are compared by a variety of algorithms,which shows that this algorithm inherits the advantages of the original MOSSE algorithm,and improves the fingerprint matching accuracy,the matching accuracy of normal images is 99%,the matching accuracy of noisy images is 90.3%,and the average calculation time of each frame is 0.1036 s,which ensures the real-time and robust nature of fingerprint tracking.It can also track deformed and rotated fingerprint images well.