A comparision of digit recognition techniques
| dc.contributor.author | Ahmad Faheem Abid | |
| dc.contributor.author | Saima Asghar | |
| dc.date.accessioned | 2013-01-12T13:39:01Z | |
| dc.date.available | 2013-01-12T13:39:01Z | |
| dc.date.issued | 2012 | |
| dc.description | Project Advisor:Mirza Mubasher Baig | en_US |
| dc.description.abstract | Optical Character recognition (OCR) has been one of the most active areas of research during the last three decades [1-4]. While automatic recognition of computer printed characters is extremely successful, and many commercial products are available for machine printed character recognition. Human are very good at recognizing the written characters and can attain 100% accuracy on neatly written characters. But the automatic recognition of human written characters is still a challenging task and we are far from perfect automatic recognition of human written characters. The task is difficult because of the unlimited variation in the writing style of people and because of the noise introduced by the digitalizing process. | en_US |
| dc.identifier.uri | https://escholar.umt.edu.pk/handle/123456789/693 | |
| dc.language.iso | en | en_US |
| dc.publisher | University of Management and Technology | en_US |
| dc.subject | BS Thesis | en_US |
| dc.subject | Digital Record | en_US |
| dc.subject | Automatic Recognition | en_US |
| dc.title | A comparision of digit recognition techniques | en_US |
| dc.title | A comparision of digit recognition techniques | en_us |
| dc.type | Thesis | en_US |
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