Reading like a human: with MVTec Deep OCR
Deep OCR is a holistic deep-learning-based approach for OCR. This new technology brings machine vision one step closer to human reading.
Compared to existing algorithms, Deep OCR can localize characters much more robustly, regardless of their orientation, font type and polarity. The ability to automatically group characters allows the identification of whole words. This strongly increases the recognition performance since, e.g., misinterpretation of characters with similar appearances can be avoided.
Through this technology big images can also be handled more robustly and the result of Deep OCR contains a list of character candidates with corresponding confidence values, which can be used to further improve the recognition results. Customers also benefit from an overall improved stability as well as from the fact that they can address a wider range of possible applications, thanks to additional character support.
Deep OCR Training
MVTec's Deep OCR enables users to efficiently solve text reading applications in a multitude of use cases. From HALCON 22.05, this technology is extended by training functionality, enabling application specific training on the user's own application dataset. This allows you to solve even most complex applications like reading text with bad contrast (e.g., on tires). Another advantage is that very rarely used special characters or printing styles can also be trained. Training for Deep OCR significantly improves the performance and usability and makes applications run even more robust.
Helpful Videos to learn how to understand and use Deep OCR
Deep OCR is available in HALCON and MERLIC, Deep OCR Training is currently only contained in HALCON. You can easily label your data in MVTec Deep Learning Tool and this data can be seamlessly integrated into HALCON.
Learn more about the other methods:
Image Classification | Object Detection | Semantic Segmentation | Edge Extraction | Instance Segmentation | Anomaly Detection