Abstract
A new concept for invariant pattern recognition is presented that uses object contour information. First, an angular signature of the object contour is obtained by a nonlinear operation applied to two-dimensional directional convolutions with a long, narrow kernel. The angular signature function is normalized by either its area or its energy to achieve quasi-invariance to scale. The resulting signature is then compared with template signatures for the invariant recognition for which an angular similarity measure is obtained from a one-dimensional correlation between the two signatures. Numerical experiments demonstrate that the method discussed exhibits invariance to shift and angular orientation and quasi-invariance to scale.
© 1993 Optical Society of America
Full Article | PDF ArticleMore Like This
Yim-Kul Lee
Appl. Opt. 33(26) 6228-6234 (1994)
Shoude Chang, Henri H. Arsenault, and Dahe Liu
Appl. Opt. 33(14) 3076-3085 (1994)
Shoude Chang, Henri H. Arsenault, Pascuala Garcia-Martinez, and Chander P. Grover
Appl. Opt. 39(35) 6641-6648 (2000)