CAJ | 학술논문

Zernike矩作为形状描述子,其信息冗余度低且对噪声不敏感,在图像特征提取和模式识别中得到了广泛应用。为提高Zernike矩对含有模糊和仿射图像的形状描述能力,提出一种基于Zernike矩的形状描述子,该描述子使用规范化方法构造Zernike矩的仿射不变量,结合Zernike矩的模糊不变量得到Zernike矩的模糊和仿射混合不变量。将该矩混合不变量作为形状描述子描述图像的形状特征,并与几何矩模糊和仿射混合不变量进行对比实验,结果表明,Zernike矩的模糊和仿射混合不变量在混合形变下形状描述能力较强,具有不变性,并且对噪声的鲁棒性较好。
Zernike구작위형상묘술자,기신식용여도저차대조성불민감,재도상특정제취화모식식별중득도료엄범응용。위제고Zernike구대함유모호화방사도상적형상묘술능력,제출일충기우Zernike구적형상묘술자,해묘술자사용규범화방법구조Zernike구적방사불변량,결합Zernike구적모호불변량득도Zernike구적모호화방사혼합불변량。장해구혼합불변량작위형상묘술자묘술도상적형상특정,병여궤하구모호화방사혼합불변량진행대비실험,결과표명,Zernike구적모호화방사혼합불변량재혼합형변하형상묘술능력교강,구유불변성,병차대조성적로봉성교호。
Zernike moment,as a shape descriptor,has been widely used in image characteristics extraction and pattern recognition. It is low information redundancy and not sensitive to noise. To improve the shape description capability of the images which are degraded by combined blur and affine transformation,a new shape descriptor based on Zernike moment is proposed. The normalization method is used to construct affine invariants of Zernike moment. The combined blur and affine moment invariants of Zernike moment is achieved by the help of the blur invariants. The combined moment invariants is used as the shape descriptor to describe the shape feature of images,and is implemented comparison with the combined affine and blur invariants based on geometric moment with relative error. Experimental results show that the combined blur and affine invariants of Zernike moment can get better shape description and invariance in combined degrades,and robustness to noise.