摘要
使用多视点特性视图方法进行易混淆三维目标识别时,由于目标具有相似的轮廓,必须辅以局部特征提取以提高识别率。传统的小波矩仅具有径向区间上的局部性,不具有角度区间上的局部性,因此提取的特征不能较好地分辨易混淆目标。利用信息采样方法,首先获得目标视图的先验信息,将目标视图分为若干个区域,由贝叶斯后验估计,分别计算基于这些区域的后验信息,然后比较其与先验信息的差异,即可获得视图中最具有分辨力的局部区域,计算这个区域上的小波矩,即可获得具有一定角度区间上的局部小波矩。研究表明,与传统的局部特征提取方法相比,这种新算法提取的局部特征具有更好的局部性,可以有效地应用于易混淆三维目标识别。
When multi-view modeling method was used in the recognition of seemingly similar 3D target, local features extraction must be added to reinforce the recognition rates for the similar contours of targets. After analyzing the localization of wavelet moment, the result was gained that wavelet moment processed the localization in the radial interval only and was a global feature in the angle interval. Firstly, the prior information of target view were obtained by using the information sampling method, and then the target view were divided into several areas. Posterior information of these areas were estimated with Bayesian Posteriors Estimation, and the differences between the prior information and posterior information were compared and the most discriminative local region was acquired at last. Wavelet moment in this local region was calculated, which make it possible to get the local wavelet moment with the localization in the angle interval. Experimental results show that, compared with the traditional methods, this proposed method can get the better localization and distinguish seemingly similar target more effectively.
出处
《红外与激光工程》
EI
CSCD
北大核心
2008年第6期1106-1110,共5页
Infrared and Laser Engineering
基金
国家自然科学基金资助项目(60575013)
航空科学基金资助项目(04I53067)
航天科技创新基金资助项目(05C53005)
关键词
易混淆三维目标识别
信息采样
局部性
小波矩
特性视图
Seemingly similar 3D target recognition
Information sample
Localization
Wavelet moment
Characteristic view
