Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Off Line Arabic Character Recognition - A Survey
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Structural Character Recognition Using Simulated Annealing
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
VIP: An FPGA-based Processor for Image Processing and Neural Networks
MICRONEURO '96 Proceedings of the 5th International Conference on Microelectronics for Neural Networks and Fuzzy Systems
Strategies in character segmentation: a survey
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
A New Robust Quadratic Discriminant Function
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Learning of Structural Descriptions of Graphic Symbols Using Deformable Template Matching
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
MSE '01 Proceedings of the 2001 International Conference on Microelectronic Systems Education (MSE'01)
Handwritten Word Recognition based on Structural Characteristics and Lexical Support
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Offline Arabic Handwriting Recognition: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Zernike wavelet moments for Farsi character recognition
Image and Vision Computing
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
Discriminant Function Revisited for Incremental Learning
ICVGIP '08 Proceedings of the 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing
An overview of character recognition focused on off-line handwriting
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Application of the ANNA neural network chip to high-speed character recognition
IEEE Transactions on Neural Networks
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This work presents an embedded Arabic OCR system. The proposed system is compact and portable which make it useful for many applications such as blind assistance and language translation. OCR system consists of the sub-systems: image acquisition, pre-processing, segmentation, feature extraction, classification, and post- processing. For each sub-system there are several of algorithms and techniques to be implemented. Working with PCs gives the designer freedom to select the algorithms and techniques according to the required performance, reliability and reusability. However with the embedded systems we are facing many problems and challenges. Such challenges are associated with memory, speed, and computational power. FPGA is selected as the hardware platform for realizing that recognition task. An OCR system is designed and implemented on PC. Then this system is transferred to FPGA after a set of optimization procedures. Utilizing the features of FPGA technology, Hardware / Software co-design is accomplished on an FPGA board. In that design the systems is partitioned into software modules and hardware components to get the advantages of software flexibility and hardware speed. A database of 3000 Arabic characters is used to train and test the performance of the system. The effects of changing the number of features and classification parameters on accuracy, memory and speed are measured. Design points are selected in order to improve the memory required, speed and computation power without affecting the accuracy.