Images matching based on a new gradient neural network

Yan Zhang; Hong-Yan Dong; Zhen-Kang Shen

doi:10.1117/12.716694

24 October 2006 Images matching based on a new gradient neural network

Yan Zhang, Hong-Yan Dong, Zhen-Kang Shen

Proceedings Volume 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence; 635709 (2006) https://doi.org/10.1117/12.716694
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China

Abstract

Focusing on the searching strategy in image matching, this paper constructs an energy function with features of a convex function based on Lyapunov Stability Theorem. It thus enables the Gradient neural network to converge steadily into the set of critical points of the target function. Then this paper tries to apply the network in image matching with moment invariants as the feature parameter. The specific steps of the experiments are supplied in this paper. According to the results of the experiments, this matching algorithm features good convergence, high speed, wide applicability and an extraordinary matching effect.

Citation Download Citation

Yan Zhang, Hong-Yan Dong, and Zhen-Kang Shen "Images matching based on a new gradient neural network", Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 635709 (24 October 2006); https://doi.org/10.1117/12.716694

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