Abstract:
Project: Optical Character Recognition. It classifies optical patterns by alphanumeric or other characters. Optic character recognition involves segmentation, feature extraction, and classification. Analog text is converted to digital text in the image. After conversion, these resources can be used as searchable text in indexes to identify documents and images.
The initial step in text capture is scanning a page. The scanned copy will form the basis for all subsequent steps. The next step is implementing Optical Character Recognition to make text machine-readable. OCR analysis translates printed or handwritten digital images into machine-readable text. For text or word or character analysis, OCR breaks the digital image into little pieces.
Again, character blocks are broken down and compared to a lexicon. This Android OCR app project has one entity: the user. Users must register with basic information and create login credentials. App login is possible after registration.
After taking an image with the camera app, the app converts the text into OCR. After finishing, users can share and save the text and image. The text or image can be shared via Android’s default share mechanism, to other system users, or as a pdf with password protection.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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