Wijaya, Erwien Tjipta and Sulaksono, Aditya Galih ORCID: https://orcid.org/0000-0003-3748-4902 (2019) Implementation of neural network and canny edge detection to recognize the crime through surveillance cameras. In: ICASI 2019, 18-19 July 2019, Banda Aceh, Indonesia.

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Abstract

The development of the smart city era in various countries is still offset by the magnitude of crime rates in every corner and downtown. Delivery of slow information to find out early crime will affect the precautions that should be taken, so as to require intelligent system-based tools. This research object is based in Jakarta Smart City (JSC) as an integrated command center with 5000 more surveillance cameras that have been installed at all strategic points in Jakarta. Surveillance cameras that have been fitted with intelligent system tools will send information to the JSC command center so that the category of criminal activity is immediately detected and immediate prevention. Among the analytical methods used are computational intelligence using Neural-network System, through video surveillance camera performed image processing using facial recognition techniques and body motion with canny edge detection algorithm segmentation. Measurement testing using a method of absolute percentage error (MAPE). So, the result level to the accuracy is 65%. Difficulty in the process of recognition because it is difficult to get the position of taking the corner of the suspect image and the victim. Implementation of intelligent system-based technology installed in surveillance cameras is expected to reduce crime rates.

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