Computer vision based detection system for defect recognition
Advanced computer vision system designed to detect defects in overlapping sheets, utilizing standard cameras for image acquisition in field conditions. This system aims to automate defect detection, thus improving efficiency and accuracy in industrial applications.
Overview
The proposed solution is a sophisticated computer vision-based detection system designed to identify and analyze defects in overlapping sheets using standard camera images. This system aims to automate the process of defect detection, which is traditionally performed manually by operators, thereby enhancing accuracy and efficiency. The technology is particularly suitable for industrial applications where precision and reliability are paramount.
Technical specifications
The system utilizes image acquisition in field conditions with standard cameras. It processes these images to detect visible defects in overlapping sheets. Key features include:
- Integration with existing hardware for seamless operation
- Image processing capabilities that analyze field-acquired data for defects
- Capability to output and report findings for further action
The project involves procuring and integrating selected hardware, including cameras and computational units, and fabricating necessary components like brackets for installation.
Technology readiness level
The technology is currently at Technology Readiness Level 3, indicating that active research and development are underway. Initial testing from field-acquired images is planned, with subsequent integration of image processing solutions with selected hardware. Further validation and adjustments are expected as the system is refined and tested in real-world conditions.
About University of Manitoba
The University of Manitoba is a comprehensive public research university in Winnipeg with a broad portfolio spanning discovery to translation. Industry engages through an on-campus research and technology park that colocates companies with university labs, and through a health sciences campus embedded in the city’s hospital district for clinical studies and clinical-grade prototyping. A well-established co-op and internship ecosystem and the region’s logistics hub position make collaboration, field trials, and pilot-scale testing accessible. Research is supported by competitive funding from NSERC, CIHR, SSHRC, and the Canada Foundation for Innovation. A dedicated technology transfer office provides IP strategy, licensing, and startup support with flexible agreements for corporate partners.
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