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by
Saleh Ali K. Al-Omari |
Total Records (
1 ) for
Saleh Ali K. Al-Omari |
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Saleh Ali K. Al-Omari
,
Putra Sumari
,
Sadik A. Al-Taweel
and
Anas J.A. Husain
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Problem statement: Handwriting number recognition is
a challenging problem researchers had been research into this area for so long
especially in the recent years.
In our study there are many fields concern with numbers, for example, checks
in banks or recognizing numbers in car plates, the subject of digit recognition
appears. A system for recognizing isolated digits may be as an approach for
dealing with such application. In other words, to let the computer understand
the Arabic numbers that is written manually by users and views them according
to the computer process. Scientists and engineers with interests in image processing
and pattern recognition have developed various approaches to deal with handwriting
number recognition problems such as, minimum distance, decision tree and statistics.
Approach: The main objective for our system was to recognize isolated Arabic
digits exist in different applications. For example, different users had their
own handwriting styles where here the main challenge falls to let computer system
understand these different handwriting styles and recognize them as standard
writing. Result: We presented a system for dealing with such problem.
The system started by acquiring an image containing digits, this image was digitized
using some optical devices and after applying some enhancements and modifications
to the digits within the image it can be recognized using feed forward back
propagation algorithm. The studies were conducted on the Arabic handwriting
digits of 10 independent writers who contributed a total of 1300 isolated Arabic
digits these digits divided into two data sets: Training 1000 digits, testing
300 digits. An overall accuracy meet using this system was 95% on the test data
set used. Conclusion: We developed a system for Arabic handwritten recognition.
And we efficiently choose a segmentation method to fit our demands. Our system
successfully designs and implement a neural network which efficiently go without
demands, after that the system are able to understand the Arabic numbers that
was written manually by users. |
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