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Automatic Number Plate Recognition (ANPR) is an intelligent system which has the capability to recognize the character on vehicle number plate. Since the past decades, many researches have been conducted to recognize the vehicle number plate and implemented it in various access control, law enforcement and security, namely parking management system, toll gate access, border access, tracking of stolen vehicles and traffic violations (speed trap). The main challenges of implementing ANPR algorithm on mobile phone are how to produce a higher coding efficiency, lower computational complexity, and higher scalability with limited CPU, memory, and camera. In this book, various steps to optimize ANPR were described, such as pre-processing, segmentation, and optical character recognition (OCR) using template matching. The proposed ANPR algorithm was based on an open source image processing library (Leptonica) and OCR library (Tesseract). This book details the step-by-step Java implementation of the proposed optimized ANPR algorithm. Results show that our proposed algorithm improved the recognition rate with negligible additional processing time.
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*Abdul Mutholib obtained his BIT from UIN Jakarta in 2007, his MSc from IIUM in 2014, and is currently a Search Engine Manager at Elevenia. *Teddy Surya Gunawan received his PhD degree from UNSW in 2007 and is currently an Associate Professor at IIUM. *Mira Kartiwi obtained her PhD from UOW in 2009 and is currently an Associate Professor at IIUM.
