ABBYY Mobile OCR Engine
Powerful mobile OCR SDK for developers
Integrate OCR into your mobile apps
ABBYY Mobile OCR Engine allows developers to integrate Optical Character Recognition (OCR) into their mobile apps and small-footprint applications. With this mobile OCR SDK, apps can extract text from photographed images, transforming smartphones and tablets into efficient mobile data capture devices.
Key features
High quality recognition in many OCR languages
Text areas and fields can be captured and data extracted directly on device.
Ready-to-use business card recognition
Pre-defined algorithms capture individual data from business card fields.
Recognition and extraction of barcode values
Several barcodes on one page can be detected, recognized and values extracted.
Key advantages
The ABBYY Mobile OCR Engine is powerful, efficient and compact. With it, applications can be made more valuable to customers by upgrading and expanding their functionality.
Superior accuracy and functionality thanks to world-renowned ABBYY OCR technology.
Low resource requirements, optimized memory management and efficient loading.
Support for multiple languages enables text recognition in 62 languages, including Latin, Cyrillic, Chinese, Japanese, Korean, and Greek.
Support for Android and iOS enables developers to widen the marketability of their applications.
Start benefiting from ABBYY Mobile OCR Engine now
How it works.
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An image is loaded from memory and prepared for OCR. Image binarization separates text from the background, producing a black-and-white image that is much smaller in size than the color original. Additional skew correction and document orientation detection can be applied.
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Document Analysis is a set of algorithms that then analyse the image. It detects letters, joins the letters into words and then into lines of text, and finally, into paragraphs. Additionally, the reading area is cleaned and noise removed.
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Detected blocks on the image are recognized using special language and pattern definitions. If dictionaries are available, then the text is also compared to them to improve overall recognition quality. Each character is assigned a confidence level – showing how confident the recognition engine was in its final choice of character.
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Recognition results can be processed and exported. The developer has full control over the OCR results.
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