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Mid Term Presentation On Optical Character Recognition. Bijay Dahal {2008/BCT/509} Kabindra Shrestha {2008/BCT/516} Raj Kumar Shrestha {2008/BCT/527}. Overview. 1. INTRODUCTION
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Mid Term PresentationOnOptical Character Recognition BijayDahal {2008/BCT/509} KabindraShrestha {2008/BCT/516} Raj Kumar Shrestha {2008/BCT/527}
Overview 1. INTRODUCTION OCR, optical character recognition refers to the branch of computer science that involves reading text from paper and translating the images into a form that the computer can manipulate. OCR systems require calibration to read a specific font; early versions needed to be programmed with images of each character, and worked on one font at a time. "Intelligent" systems with a high degree of recognition accuracy for most fonts are now common. Some systems are capable of reproducing formatted output that closely approximates the original scanned page including images, columns and other non-textual components. While saving the books and documents, it will save in image file. Which will takes more space than txt file. The file is not editable. There is problem of loading time to publish the image file on a website. Text can be printed in larger size but image generate a distorted quality. Alpha-numeric character ->normal text files To make document editable.
Get Image Binarization Noise Reduction Thinning System Architecture Save Text Pattern Matching Text Segmentation Skew Detection
Algorithms Ostu Binarization Algorithm Skeleton Thinning Algorithm Generic Segmentaion Algorithm
Completed Activities Proposal Submission GUI (For Testing) Coding Image Binarization Line Segmentation Character Segmentation
Challenges Faced Time Limitation Choosing the correct algorithm. Hard to code algorithm. If coded output is not accurate. For text segmentation we use own methods.