Maximum Average Correlation Height Filter Based on Pulsed Neural Network for Distorted Target Recognition

Xiang Li; Dong Ming Zhou; Ren Can  Nie; Hai Ying Deng; Hong Mei Li

doi:10.4028/www.scientific.net/AMM.380-384.3846

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 380-384Maximum Average Correlation Height Filter Based on...

Maximum Average Correlation Height Filter Based on Pulsed Neural Network for Distorted Target Recognition

Abstract:

A novel method for image recognition using Pulsed Coupled Neural Network (PCNN) based on Maximum Average Correlation Height (MACH) filtering is proposed. Firstly based on the property of synchronous pulses oscillation for the similar group of neurons in PCNN, segment image to extract edge information, and this effectively suppresses noise. Subsequently the synthesized MACH is adopted to excellently realize the distorted target recognition using appropriate filter parameters depending on different targets. The simulations results show that the output correlation peak is obvious, and validate the effectiveness and accuracy of the method for distortion target recognition.

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Periodical:

Applied Mechanics and Materials (Volumes 380-384)

Pages:

3846-3849

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.380-384.3846

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Online since:

August 2013

Authors:

Xiang Li, Dong Ming Zhou, Ren Can Nie, Hai Ying Deng, Hong Mei Li

Keywords:

Maximum Average Correlation Height (MACH) Filter, Pulsed Coupled Neural Network, Recognition of Distortion Target

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References

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