Ladar range images have attracted considerable attention in automatic target recognition fields. In this paper, Zernike moments (ZMs) are applied to classify the target of the range image from an arbitrary azimuth angle. However, ZMs suffer from high computational costs. To improve the performance of target recognition based on small samples, even-order ZMs with serial-parallel backpropagation neural networks (BPNNs) are applied to recognize the target of the range image. It is found that the rotation invariance and classified performance of the even-order ZMs are both better than for odd-order moments and for moments compressed by principal component analysis. The experimental results demonstrate that combining the even-order ZMs with serial-parallel BPNNs can significantly improve the recognition rate for small samples.
© 2012 Optical Society of America
Original Manuscript: April 18, 2012
Revised Manuscript: August 30, 2012
Manuscript Accepted: September 14, 2012
Published: October 24, 2012
Zheng-Jun Liu, Qi Li, Zhi-Wei Xia, and Qi Wang, "Target recognition of ladar range images using even-order Zernike moments," Appl. Opt. 51, 7529-7536 (2012)