1 / 5

Optical Character Recognition

OCR using Machine Vision is commonly used to read characters printed on packaging labels, currency, credit cards, automotive parts like chassis, etc. Basically used for the purpose of identification, verification, tracing and tracking of character codes and data.

qualitas
Télécharger la présentation

Optical Character Recognition

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Optical Character Recognition Why work with a vision system integrator Read complex characters with varying fonts and challenging backgrounds using cutting edge Artificial Intelligence technology Qualitas Technologies has developed an Optical Character Recognition (OCR) solution based on cutting edge Artificial Intelligence (AI) technology. OCR using Machine Vision is commonly used to read characters printed on packaging labels, currency, credit cards, automotive parts like chassis, etc. Basically used for the purpose of identification, verification, tracing and tracking of character codes and data. Machine Vision OCR technology can also be used for ensuring the correctness of labels that are printed, this is especially important in pharmaceutical manufacturing. Benefits: The main differentiators over traditional OCR technologies is that:  Easy to train using a point and click interface  It can read any style of character even if images differ in characteristics from the trained ones.

  2. Much higher accuracies, comparable to human read rates, but with much faster processing time Multiple fonts can be easily supported   Our solution uses Deep Learning for character recognition Our solutions are running successfully across a variety of different industries and applications. Some images are shown as an illustrative example below. Images Captured by the Vision System

  3. The below example is where we’re using the latest deep learning technology to read complex and difficult to read characters. Deep Learning has been successful in achieving over 98% read rates, with over 97% accuracy in reading errors. Read More: https://bit.ly/3dsBOAF

More Related