Optical character recognition is an evergreen area of research and is verily used in various real time applications. This paper proposes a new technique of optical character recognition using Gabor filters and support...
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Optical character recognition is an evergreen area of research and is verily used in various real time applications. This paper proposes a new technique of optical character recognition using Gabor filters and support vector machines (SVM). This method proves to be very effective with the use of Gabor filters for feature extraction and SVM for developing the model. The model proposed is trained and validated for two languages - English and Tamil and the results are found to be very much encouraging. The model developed works for the entire character set in both the languages including symbols and numerals. In addition , the model can recognise the characters of six different fonts in English and Twelve different fonts in Tamil. The average accuracy of recognition for English is 97% and for Tamil it is 84%, which is achieved in just three iterations of training. The method can turn out to be a suitable candidate for future applications in this area.
Optical character recognition (OCR) is a classical research field and has become one of most thriving applications in the field of pattern recognition. Feature extraction is a key step in the process of OCR, which in ...
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Optical character recognition (OCR) is a classical research field and has become one of most thriving applications in the field of pattern recognition. Feature extraction is a key step in the process of OCR, which in fact is a deciding factor of the accuracy of the system. This paper proposes a novel and robust technique for feature extraction using Gabor Filters, to be employed in the OCR. The use of 2D Gabor filters is investigated and features are extracted using these filters. The technique generally extracts fifty features based on global texture analysis and can be further extended to increase the number of features if necessary. The algorithm is well explained and is found that the proposed method demonstrated better performance in efficiency. In addition, experimental results show that the method gains high recognition rate and cost reasonable average running time.
This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* ...
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ISBN:
(数字)9783642291784
ISBN:
(纸本)9783642291777
This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2012, held in Málaga, Spain, in April 2012, colocated with the Evo* 2012 events EuroGP, EvoCOP, EvoBIO, and EvoMUSART. The 54 revised full papers presented were carefully reviewed and selected from 90 submissions. EvoApplications 2012 consisted of the following 11 tracks: EvoCOMNET (nature-inspired techniques for telecommunication networks and other parrallel and distributed systems), EvoCOMPLEX (algorithms and complex systems), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoHOT (bio-inspired heuristics for design automation), EvoIASP (evolutionary computation in image analysis and signal processing), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defense applications), EvoSTIM (nature-inspired techniques in scheduling, planning, and timetabling), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).
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