Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/33873
Title: New crime detection with LBP and GANN
Authors: Ahmad Kadri, Junoh
Muhammad Naufal, Mansor
kadri@unimap.edu.my
apairia@yahoo.com
Keywords: Crime rate
Feed Forward Neural Network
Genetic Algorithm Neural Network
Local Binary Pattern
Issue Date: 2013
Publisher: Springer-Verlag
Citation: Advances in Intelligent Systems and Computing, vol. 206 AISC, 2013, pages 655-660
Abstract: A current review of media sources indicates crimes of opportunity such as burglaries, purse-snatchings and vehicle theft, are consistently the most topical crime problems. The Malaysian government has taken several steps to increase police effectiveness and reduce crime since 2004. But their effectiveness is limited by low salaries and lack of manpower. Verily to compile a comprehensive afford of crime fighting capabilities. We present an explicit system to detect a crime scene with Local Binary Pattern (LBP) and a fusion of Genetic Algorithm with Neural Network (GANN). This system provided a good justification as a monitoring supplementary tool for the Malaysian police arm forced.
Description: Link to publisher's homepage at http://link.springer.com/
URI: http://link.springer.com/chapter/10.1007%2F978-3-642-36981-0_60
http://dspace.unimap.edu.my:80/dspace/handle/123456789/33873
ISBN: 978-364236980-3
ISSN: 2194-5357
Appears in Collections:Institute of Engineering Mathematics (Articles)

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