The use of artificial intelligence in OCR and OCV analysis ensures outstanding efficiency and accuracy in text recognition. OCR (Optical Character Recognition) converts various labels, marks, and images into editable and readable text. By using advanced algorithms, OCR enables the digitization and processing of large volumes of data efficiently, thereby improving accuracy in product identification and tracking. Additionally, it facilitates integration with inventory and logistics management systems, optimizing operational flow.
On the other hand, OCV (Optical Character Verification) complements OCR by ensuring that all printed elements are perfectly legible and correct, which is crucial for regulatory compliance and preventing costly errors.
Reading is optimized with artificial intelligence and GPU (optional), achieving rapid text recognition at speeds of up to 180,000 u/h.
Both technologies not only increase the efficiency and productivity of production lines but also contribute to waste reduction and improved safety, making each stage of the industrial process more robust and reliable.
The VisioInspect 2.0 vision software, developed by E2M COUTH, with industrial OCR and OCV analysis, offers exceptional capabilities such as:
- Precise segmentation: The system offers both automatic and manual segmentation for different texts and conditions.
• Advanced recognition: Utilizes MLP (multilayer perceptrons), CNN (convolutional neural networks), and AI with Deep Learning for complex conditions.
• Optional verification (OCV): Allows confirmation that the recognized text is correct without defining each character individually.
• Reading from multiple sources such as print fonts, dot-matrix printing, and handwritten texts.
• Reading speed: Optimized via GPU in AI applications, adapting to various production speeds (reading two lines with dates, up to 180,000 u/h).
• Adaptability: Capable of reading text under various conditions, such as tilted, blurred, or distorted text.
