As mobile devices processing power have been evolved and improved significantly, and cameras became more sophisticated, the outstanding quality of the produced images, revealed that those devices could not only be used to take ordinary photos but also to transform your mobile phone or tablet into a powerful capture device.
Modern devices have much more computing power compared with the old workstations used to scan documents. So, it means that with a mobile device we can capture photos, documents, apply filters, transform and normalize images and even use other technologies such as (OCR) Optical Character Recognition and Bar Code Recognition to extract information from captured images. Additionally, these devices can also be used to perform advanced computer vision and machine learning algorithms to match image patterns in order to identify faces, emotions, shapes, objects and even documents, all in real time!
Given this scenario, iCapt has experienced, tested and blended several algorithms and image processing features into a custom library that represents the core component of the Mobile Capture Framework.
These are the challenges and issues that we have addressed with our Framework:
- Auto snap photos based on custom triggers, such as document aspect ratio, document size, face position, gestures (blinking), barcode type and position, etc.
- Image scale normalization based on the actual physical document size
- Classify images out of scale and in perspective, a very common issue with photos captured by mobile devices
- Embed 3rd components to provide integrated features, such as face matching and OCR
- Embed rules bases classification and data extraction features
If you need to build a custom SDK that needs to encapsulate specific image processing and data capture components, just let us know.
If you need further information, please send an e-mail to firstname.lastname@example.org