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On the parallelization of closed-set patterns classification for an automatic license plate recognition system

Abstract

One of the objectives for a smart city is by applying the fast car retrieval system, which requires the tracking of a vehicle LP (License Plate) using a detection sensor system. ALPR (automatic license plate recognition) system is important through different walks of life, such as: security, access control, and law enforcement in traffic violation systems. In a previous work [1], multiple closed-set patterns belonging to the Saudi LP are extracted and classified using classification and clustering techniques. A reasonable delay in time is accumulated while extracting the image features before being categorized to a certain cluster. A problem arises that we are not able to process the amount of information in real-time, therefore it is crucial to reduce processing time. The solution is by applying the parallelization processes that enables the online processing of images by an embedded system

Author(s)

Salah Al-Shami

Coauthor(s)

Ahmed Ahmed Zekri, Ali Yassine El-Zaart, Rached Rached Zantout

Journal/Conference Information

Sensors Networks Smart and Emerging Technologies (SENSET), 2017,Conference Type: International, Location: Beirut, Lebanon, Organized By: Lebanese University, Proceeding Format: Electronic editions, Conference Date: 9/14/2017,