Abstract
In this paper, an Optical Character Recognition system for printed/scanned Pashto continuous text is presented. The proposed Pashto optical character recognition system uses a Feed Forward Neural Network (FFNN), consisting of an input layer, a hidden layer and an output layer. The input layer is composed of 315 neurons, which receive the pixels data i.e. binary data from a 21x15 symbol pixel matrix. The hidden layer contains 2000 neurons which has been chosen after testing based on optimal result, while the output layer is composed of 6 neurons. As the joinable Pashto characters on different locations in text change its size and shapes, as a result 60 Pashto characters with 110 samples for each Pashto character has been used to train the network.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
