Abstract
Optical character recognition of Arabic language is a field of research that is socially very relevant and challenging.The social relevance lies on the fact that OCR is very important for many applications that need character recognition of images. Our system is Egyptian ID cards reader system which extracts important data from the ID card image, recognizes data and translates it into editable text on computer so it can be edited and saved. Then, the system can compare between a tested ID card and the database saved before. This paper extensively reviews the base line-based segmentation and DCT based feature extractor approaches used for building this special Arabic OCR system. It also reports the experimental results obtained so far showing the reliability of our system. Finally, we’ll show thatthe system works fast on the scientific Matlab library, as it needs about 16 seconds in average to process one ID card, and the system is expected to do better performance when transferring it from the academic phase to the product phase.
Highlights
Humans recognize characters and they repeat the character recognition process thousands of times every day as they read papers or books [1]
From the realization of the importance of such applications and their impact on the society, this paper shows developing an Arabic optical character recognition (OCR) system dedicated for ID card recognition
Arabic OCR Challenges working on a standard ID has advantages like, the font type is fixed and approximately similar font sizes, Arabic words may horizontally overlap and could not be separated; i.e., letters may stack on others
Summary
Humans recognize characters and they repeat the character recognition process thousands of times every day as they read papers or books [1]. After many years of serious investigation and research, the ultimate goal of developing an optical character recognition (OCR) system, with the same interpretation capabilities as humans, still remains unachieved. OCR allows the machine automatically to recognize characters in an image and translate them into computer textual format by applying machine learning mechanism. Different OCR engines allow the machine to automatically recognize characters in an image and translate them into computer textual format by applying machine learning mechanism. This improves human-machine interaction and is widely used in many areas [6], [9]. Applications and their impact on the society, this paper shows developing an Arabic OCR system dedicated for ID card recognition.
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