A2iA, the worldwide leading developer of handwritten and machine printed text recognition, information extraction and intelligent classification of paper documents, recently announced enhancements to its A2iA CheckReader™ toolkit. A2iA CheckReader, a set of advanced image analysis and intelligent recognition engines, is trusted worldwide by thousands of end users in solutions for branch capture, merchant applications, point-of-deposit applications, fraud detection, ATMs, centralized and de-centralized capture, remittance applications, image quality analysis (IQA) and image usability analysis (IUA). By providing software applications the ability to capture handwritten and machine-printed information from all areas of checks and related payment documents, A2iA CheckReader reduces manual labor and improves business process automation. Handwritten data is no longer out-of-reach and paper documents can now be turned into meaningful information and integrated into information technology systems.
This most recent release provides for enhanced recognition and image quality analysis for the product's 23-country versions, which are available in six languages including English, Spanish, Portuguese, French, Italian and German.
All A2iA CheckReader country-versions now support recognition of printed fields with OCR-7B font, as well as the below enhancements and features:
A2iA, Artificial Intelligence and Image Analysis, is a software company that operates one of the world's largest research centers focusing on ways to extract information from everyday paper documents that contain handwritten information. A2iA's Document Classification, OCR, ICR and IWR technologies have been reducing data-entry costs and improving business process automation for nearly 20 years. A2iA recognition engines can be used to enhance the forms processing, transaction processing, business process management, record-management, e-discovery, content management, document management, and knowledge management systems from leading vendors.
SOURCE: A2iA Corporation