Everything you need to easily build scanning capabilities into your mobile applications
The Android OCR is ready to be used in Android projects right away! We offer dedicated support, free updates during the license runtime and continuous improvements. We are actively developing and releasing new features for the Android OCR.
Optical Character Recognition has been enabled scanned documents to become more than just image files, turning into fully searchable documents with text content that is recognized by computers. OCR usage, decreases the peoples work of manually retype important documents again ,when entering them into electronic databases. Instead, OCR extracts relevant information and enters it automatically. The result is accurate, efficient information processing in less time.
The uses of Optical Character Recognition vary across different fields. OCR application mostly used in banking, where OCR is used to process checks without human involvement. A check can be inserted into a machine, the writing on it is scanned instantly, and the correct amount of money is transferred. It’s mostly helpful perfectly for printed checks, and is very accurate for handwritten checks, though it occasionally requires manual confirmation. Overall, this reduces wait times in many banks.
Applications
Traffic & transportation industry
Container number identification
License plate recognition system
Automatic recording of the text written on the vehicle surface
Industrial inspection
Document imaging
Features of OCR
Capability:Robust across different font types, sizes, symbols Ability to segment and recognize characters, words, text lines, paragraphs and full pages Ability to split and recognize glued characters, as well as to glue and recognize broken characters Hi-performance OCR engine, with pre-processing and de-skewing and normalization techniques.
Speed: 200 to 600 Characters Per Second (CPS)is readily achievable depending on the CPU speed.
Accuracy: 100% accuracy is achievable when the print and image quality is good. With drop in image quality, the accuracy drops gracefully, and can be better than or close to what human beings can read.
Input: Gray scale or bi-tonal images with a 200 DPI or greater resolution can be used as input. Custom solutions have been built around OCR on videos, integrating frames with varying text resolution (and motion blur).
Output: The output includes ASCII or UNICODE character strings, and confidence values (for decision/data fusion). We have also combined character level output to interpret word or higher level data.
Platform: The OCR Engine supports Linux and Windows based platforms. Custom embedded platform implementations have also been made, optimized for memory and run-time.
Optical Character Recognition has been enabled scanned documents to become more than just image files, turning into fully searchable documents with text content that is recognized by computers. OCR usage, decreases the peoples work of manually retype important documents again ,when entering them into electronic databases. Instead, OCR extracts relevant information and enters it automatically. The result is accurate, efficient information processing in less time.
The uses of Optical Character Recognition vary across different fields. OCR application mostly used in banking, where OCR is used to process checks without human involvement. A check can be inserted into a machine, the writing on it is scanned instantly, and the correct amount of money is transferred. It’s mostly helpful perfectly for printed checks, and is very accurate for handwritten checks, though it occasionally requires manual confirmation. Overall, this reduces wait times in many banks.
Applications
Traffic & transportation industry
Container number identification
License plate recognition system
Automatic recording of the text written on the vehicle surface
Industrial inspection
Document imaging
Features of OCR
Capability:Robust across different font types, sizes, symbols Ability to segment and recognize characters, words, text lines, paragraphs and full pages Ability to split and recognize glued characters, as well as to glue and recognize broken characters Hi-performance OCR engine, with pre-processing and de-skewing and normalization techniques.
Speed: 200 to 600 Characters Per Second (CPS)is readily achievable depending on the CPU speed.
Accuracy: 100% accuracy is achievable when the print and image quality is good. With drop in image quality, the accuracy drops gracefully, and can be better than or close to what human beings can read.
Input: Gray scale or bi-tonal images with a 200 DPI or greater resolution can be used as input. Custom solutions have been built around OCR on videos, integrating frames with varying text resolution (and motion blur).
Output: The output includes ASCII or UNICODE character strings, and confidence values (for decision/data fusion). We have also combined character level output to interpret word or higher level data.
Platform: The OCR Engine supports Linux and Windows based platforms. Custom embedded platform implementations have also been made, optimized for memory and run-time.
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