基于扇区投影-小波描述子的图像轮廓识别

Contour Recognition Using Sector-projection-wavelet-descriptor

针对传统轮廓描述子不能识别相似样本或者确定图像方向复杂等一系列缺陷,本文提出了基于主轴归一化方法的轮廓扇区投影-小波描述子。该方法根据图像识别中的畸变不变性原理,采用先位置、大小、方向归一化,后扇区投影和小波分析的方法。该描述子不仅能消除掉主轴归一化方法的不精确性对轮廓描述的影响,而且还能够解决傅里叶描述子和环投影方法不能解决的一些特殊轮廓样本的分类问题。实验结果表明,无论是差别比较大的轮廓样本还是差别细微的轮廓样本,扇区投影-小波描述子都有着很好识别效果。

Aiming to the defects that some traditional contour descriptors can＇t classify similar contours and that others o not have a good internal rotation-invariant property, the sector-projection-wavelet-descriptor was proposed. Contour to be recognized was first orientation normalized by its principal axis. And then, the normalized contour was projected on the prepared N-sector-areas. Finally, the curve gotten from previous steps was analyzed by wavelet theory. This descriptor can not only decrease the error caused by orientation normalization, but also can classify some contours which can not be classified by ring-projection or Fourier descriptor. The experiments compared with other contour descriptors show： sector-projection-wavelet-descriptor has a good recognition result whatever the contours to be classified are similar or largely different.