Improved Genetic Algorithm to Calibration of the Pulse Coupled Neural Network Parameter

Rui Cheng Feng; Hai Yan Li; Zhi Yuan Rui; Rui Sheng Chen; Bao Cheng Zhou

doi:10.4028/www.scientific.net/AMR.694-697.1993

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 694-697Improved Genetic Algorithm to Calibration of the...

Improved Genetic Algorithm to Calibration of the Pulse Coupled Neural Network Parameter

Abstract:

Based on the research of PCNN algorithm,details the basic idea of the genetic algorithm, introduction of genetic algorithm for optimal family.In order to verify the effectiveness of the algorithm,implements the algorithm and comparison algorithm on the PC with the VS2008, CUDA, OpenCV 2.2.The experimental results showed that:Improved PCNN algorithm to better deal with the multi-modal regional background,improve the accuracy of moving object segmentation.Effectively filter interference prospects at the same time,complete retention of the shape, the edge information of the moving object.In this paper, the improved genetic algorithm can guarantee the quality of motion detection, and provide a guarantee for the the subsequent image recognition accuracy.

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Periodical:

Advanced Materials Research (Volumes 694-697)

Pages:

1993-1997

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.694-697.1993

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Online since:

May 2013

Authors:

Rui Cheng Feng, Hai Yan Li, Zhi Yuan Rui, Rui Sheng Chen, Bao Cheng Zhou

Keywords:

Genetic Algorithm (GA), Motion Detection, Optimal Family Genetic Algorithm, Pulse Coupled Neural Network

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