Number Plate Detection with a Multi-Convolutional Neural Network Approach with Optical Character Recognition for Mobile Devices

Christian Gerber and Mokdong Chung
Volume: 12, No: 1, Page: 100 ~ 108, Year: 2016
10.3745/JIPS.04.0022
Keywords: Convolutional Neural Network, Number Plate Detection, OCR
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Abstract
In this paper, we propose a method to achieve improved number plate detection for mobile devices by applying a multiple convolutional neural network (CNN) approach. First, we processed supervised CNN- verified car detection and then we applied the detected car regions to the next supervised CNN-verifier for number plate detection. In the final step, the detected number plate regions were verified through optical character recognition by another CNN-verifier. Since mobile devices are limited in computation power, we are proposing a fast method to recognize number plates. We expect for it to be used in the field of intelligent transportation systems.

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Cite this article
IEEE Style
Christian Gerber and Mokdong Chung, "Number Plate Detection with a Multi-Convolutional Neural Network Approach with Optical Character Recognition for Mobile Devices," Journal of Information Processing Systems, vol. 12, no. 1, pp. 100~108, 2016. DOI: 10.3745/JIPS.04.0022.

ACM Style
Christian Gerber and Mokdong Chung, "Number Plate Detection with a Multi-Convolutional Neural Network Approach with Optical Character Recognition for Mobile Devices," Journal of Information Processing Systems, 12, 1, (2016), 100~108. DOI: 10.3745/JIPS.04.0022.