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- Title
Improved combined invariant moment for moving targets classification.
- Authors
Chen, Xiao-jun; Ke, Jia; Zhan, Yong-zhao; Chen, Xiao-bo; Zhang, Qian-qian; Jiang, Xiao-ming; Song, Xin-ping; Chen, Bao-ding; Xu, Hui; Zhang, Jian-guo
- Abstract
Invariant moment is a highly concentrated and distortion invariant image features. The goal of multi-moving object characterization and classification methods is to find a suitable description of different kinds of moving objects in the scene and match the similarity between unknown moving objects with invariant moment. This paper presents evolution and development of invariant moments family history, and designs a classification model to classify multi-moving objects. Experimental results show that this method can effectively improve the recognition rate of the moving object.
- Subjects
IMAGE recognition (Computer vision); IMAGE reconstruction algorithms; EUCLIDEAN geometry; ARTIFICIAL neural networks; DEEP learning
- Publication
Multimedia Tools & Applications, 2017, Vol 76, Issue 19, p19959
- ISSN
1380-7501
- Publication type
Article
- DOI
10.1007/s11042-016-4014-x