基于正交矩模糊和仿射混合不变量的图像识别算法

Image recognition algorithm based on combined blur and affine invariants of legendre moment

为了识别含有模糊和仿射混合形变的图像,提出了一种新的基于正交矩模糊和仿射混合不变量的图像识别算法.该算法首先使用归一化方法构造了基于Legendre正交矩的仿射不变量,并结合Legendre正交矩的模糊不变量提出了Legendre正交矩的模糊和仿射混合不变量;然后将该混合不变量作为描述算子,将欧几里德范数作为分类尺度,以最近邻法则作为分类器,对图像进行识别.实验结果表明,与其他基于非正交矩的混合不变量相比,基于Legendre正交矩的模糊和仿射混合不变量在混合形变下能够获得更好的不变性,不会带来信息冗余问题,并且对噪声鲁棒性较好;此外,该图像识别算法比其他算法具有更高的识别率,特别是在图像含有较大噪声的情况下.

To recognize the images distorted by combined blur and affine transformation,a new image recognition algorithm based on combined blur and affine invariants of orthogonal moment is proposed.In this algorithm,the normalization method is used to construct affine invariants of orthogonal Legendre moment.The combined blur and affine moment invariants of orthogonal Legendre moment is proposed with the help of the blur invariants.Then the new combined invariants,the Euclidean norm and nearest neighbor rules are taken as the descriptors,the measurement of classification and classifier respectively to recognize the image.The experimental results show that compared with the non-orthogonal moment invariants,the combined blur and affine invariants of orthogonal Legendre moment can achieve better invariance,less redundant information and better robustness to noise.Furthermore,this algorithm can obtain higher recognition rates,especially when the images are heavily corrupted by noise.