正交Fourier-Mellin矩模糊不变量的构造及应用  

Construction and Application of Blur Invariants Based on Orthogonal Fourier-Mellin Moment

作　　者：戴修斌[1] 刘天亮[2] 舒华忠[3] 罗立民[3] 

机构地区：[1]南京邮电大学地理与生物信息学院,南京210046 [2]南京邮电大学通信与信息工程学院,南京210003 [3]东南大学计算机科学与工程学院,南京210096

出　　处：《应用科学学报》2013年第5期495-502,共8页Journal of Applied Sciences

基　　金：国家自然科学基金(No.31200747);江苏省自然科学基金(No.BK2012437);南京邮电大学引进人才科研启动基金(No.NY211030)资助

摘　　要：为了有效识别含有模糊形变的图像或特征,构造了正交Fourier-Mellin矩模糊不变量.通过获得形变图像和理想图像正交Fourier-Mellin矩之间的关系,推导出基于正交Fourier-Mellin矩函数的模糊不变量,然后利用该模糊不变量识别形变图像.实验表明,在不同模糊形变和不同强度噪声作用下,正交Fourier-Mellin矩模糊不变量的不变性均优于其他不变量,且对模糊形变图像的正确识别率更高.We propose a new set of blur invariants based on orthogonal Fourier-Mellin moments to effec- tively recognize blurred images. We establish the relationship between orthogonal Fourier-Mellin moments of the original and distorted images. We then use this relationship to construct blur invariants of orthogonal Fourier-Mellin moment. The new blur invariants are used as feature descriptors to recognize blurred images. Experimental results show that, with different kind of blur degradation and different densities of noises intro- duced into the images, better invariance and higher recognition rates can be obtained by using the proposed invariants as compared to other blur invariants.

关 键 词：模糊图像识别 模糊不变量 正交Fourier—Mellin矩 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]