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Proceedings Paper

Combining blur and affine moment invariants in object recognition
Author(s): Yingchun Li; Hexin Chen; Jiujun Zhang; Pengfei Qu
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Paper Abstract

In many application areas such as military photointerpretation and remote sensing, images are usually subjected to geometric distortion and blur degradation. The determination of invariant characteristics is an important problem in pattern recognition. In this paper, an approach to derive blur and affine combined invariants is presented to recognize the objects. As we prove in the paper, they can be constructed by combining affine moment invariants and blur invariants derived earlier. The tests show that combined invariants can recognize objects in the degraded image without any restoration and geometric normalization.

Paper Details

Date Published: 2 September 2003
PDF: 6 pages
Proc. SPIE 5253, Fifth International Symposium on Instrumentation and Control Technology, (2 September 2003); doi: 10.1117/12.521525
Show Author Affiliations
Yingchun Li, Jilin Univ. (China)
Hexin Chen, Jilin Univ. (China)
Jiujun Zhang, Second Aeronautical Institute of the Air Force (China)
Pengfei Qu, Second Aeronautical Institute of the Air Force (China)


Published in SPIE Proceedings Vol. 5253:
Fifth International Symposium on Instrumentation and Control Technology
Guangjun Zhang; Huijie Zhao; Zhongyu Wang, Editor(s)

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