OCR (Optical Character Recognition) technology is becoming more and more popular in data entry. Nowadays it has been used by lots of companies, including telecom company, social networks, mobile phone manufacturers and more. OCR technology is mainly used to recognize characters in document images or card images, and help people reduce entry time.
Banking Card Recognition SDK, developed by Yunmai Technology, gives their application an easy way to extract data from card images. It can be generally applied to the industries which deal with a lot of bank card information entries. Integrating Banking Card Recognition SDK into your software or application to provide software-based credit card payment solution for people.
Nowadays, more and more people feel like shopping online through mobile phone. In the meantime, it is important to simplify mobile operating procedures to promote mobile phone payment. During online shopping, sometimes they need to input bank card information to pay for goods. It may take longer time for them to retype the card number and other information. They may also make some mistakes during retyping.
Developing an application with OCR technology can help them easily input the card information without having to retype it. They just need to capture the bank card with mobile camera's device. Integrating Banking Card OCR SDK into the software or application will automatically recognize the card and extract the information on it. It can also categorize the content on the card, such as the bank name, the card number and the expiration date.
Demo application of Bank Card OCR SDK
Now the Yunmai has released Bank Card Recognition which is a demo mobile application of bank card OCR SDK, you can go to Yunmai’s product downloads site to get an app for trial.
Accuracy rate and OCR engine efficiency (reference)
- Bank card recognition accuracy
The average recognition accuracy rate for the Banking Card is 99%.
- OCR SDK efficiency
The engine process recognizing a Banking Card will take about 0.15 seconds for average.
Programming language supported
The OCR SDK is available for different programming languages: Java, C++, C, Object Pascal, Objective-C.
Other recognition SDKs we developed
Document OCR SDK
Chinese ID card recognition SDK
Business card recognition SDK
2016年2月26日星期五
2016年2月18日星期四
Document OCR SDK
Yunmai Document OCR SDK provides Optical Character Recognition technology for developers. By integrating our recognition SDK, your software is able to extract text from images, and create editable documents. This feature is generally used to manage a large amount of paper documents. The SDK can be integrated into mobile application or PC software.
What the OCR SDK can do
- Extract text from image: Identify the characters on the image and retrieve the text.
- Automatically crop image: Automatically detect document position and trim edges before running the text identification.
- Character suggestion: After the Optical Character Recognition is completed, the engine is able to automatically detect potential errors on the recognition results, and provide characters suggestion and words suggestions. For English, the engine will give both characters and words; for Chinese, Chinese characters will be provided.
- Export to PDF: Export to double-layer PDF file to allow user to search content within the file by typing keyword.
- Auto categorization of images: After scanning images, the engine is able to automatically detect picture type and categorize the images before running OCR. The possible categories are: Business card, ID card, passport, license, text document, landscape, etc.
- Blur detection: Before the text recognition, the engine will analyze the image quality and define whether the picture is blurry or not.
- Image format supported: jpg, png, bmp. The engine supports manual adjustments of the image effects, such as brightness, contrast, color mode, etc.
- Support multiple languages: Simplified Chinese, Traditional Chinese, English, Spanish, French, German, Italian, Portuguese, Swedish, Danish, Norwegian, Finnish and Dutch.
How the text extractor works
Step 1: Capture paper document or import existing image;
Step 2: Crop image, and enhance image effects;
Step 3: Process OCR to extract text from the image;
Step 4: Use character suggestion to correct errors or manually edit the results.
Demo application of Document OCR SDK
Docs Matter - Document ......
Character recognition results
The following are the average recognition accuracy for different languages:
English characters: 97%
European characters: 99%
Chinese characters: 92%
These data are obtained on recognizing an 8 pixel megabytes image of a document with 800 characters, and the font size is 12.
Character recognition speed
The recognition speed is based on hardware and the document captured, the following is an example:
Hardware: 1.7GHz CPU / 1GB RAM smart phone or higher
Capturing object: a paper document with about 800 characters
Recognition speed: OCR process will take about 7 seconds.
Programming language supported
The SDK is available for different programming languages: Java, C++, C, Object Pascal, Objective-C.
Other recognition SDKs we developed
Business card recognition SDK
Bank card recognition SDK
Chinese citizen ID card recognition SDK
What the OCR SDK can do
- Extract text from image: Identify the characters on the image and retrieve the text.
- Automatically crop image: Automatically detect document position and trim edges before running the text identification.
- Character suggestion: After the Optical Character Recognition is completed, the engine is able to automatically detect potential errors on the recognition results, and provide characters suggestion and words suggestions. For English, the engine will give both characters and words; for Chinese, Chinese characters will be provided.
- Export to PDF: Export to double-layer PDF file to allow user to search content within the file by typing keyword.
- Auto categorization of images: After scanning images, the engine is able to automatically detect picture type and categorize the images before running OCR. The possible categories are: Business card, ID card, passport, license, text document, landscape, etc.
- Blur detection: Before the text recognition, the engine will analyze the image quality and define whether the picture is blurry or not.
- Image format supported: jpg, png, bmp. The engine supports manual adjustments of the image effects, such as brightness, contrast, color mode, etc.
- Support multiple languages: Simplified Chinese, Traditional Chinese, English, Spanish, French, German, Italian, Portuguese, Swedish, Danish, Norwegian, Finnish and Dutch.
How the text extractor works
Step 1: Capture paper document or import existing image;
Step 2: Crop image, and enhance image effects;
Step 3: Process OCR to extract text from the image;
Step 4: Use character suggestion to correct errors or manually edit the results.
Demo application of Document OCR SDK
Docs Matter - Document ......
Character recognition results
The following are the average recognition accuracy for different languages:
English characters: 97%
European characters: 99%
Chinese characters: 92%
These data are obtained on recognizing an 8 pixel megabytes image of a document with 800 characters, and the font size is 12.
Character recognition speed
The recognition speed is based on hardware and the document captured, the following is an example:
Hardware: 1.7GHz CPU / 1GB RAM smart phone or higher
Capturing object: a paper document with about 800 characters
Recognition speed: OCR process will take about 7 seconds.
Programming language supported
The SDK is available for different programming languages: Java, C++, C, Object Pascal, Objective-C.
Other recognition SDKs we developed
Business card recognition SDK
Bank card recognition SDK
Chinese citizen ID card recognition SDK
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