Traditional computer vision (CV) relies on rule-based algorithms to analyze images, utilizing techniques like filtering, edge detection, and pattern matching to interpret shapes, shading, textures, and more. These techniques have long been the foundation for extracting value from camera sensors in manufacturing settings.
Unlocking AI Inspections Starts with Traditional CV
Traditional CV plays a crucial role in helping manufacturers add comprehensive and standardized quality inspection to their machines and lines. Our OneView software illustrates how integrating traditional CV with AI can expedite value generation, reduce the reliance on expert-driven tasks and enhance overall system efficiency.
Here’s how we do it:
- Early Deployment of Traditional CV: We start with traditional CV to quickly improve quality outputs while simultaneously isolating image data for human review, which is crucial for training AI models.
- Incorporating Anomaly Detection: Adding anomaly detection to the CV-detected defects focuses on identifying what good looks like. This process helps further segregate data, highlighting outliers that traditional CV can miss.
- Implementing Supervised AI Models: The final step involves using AI-supervised classification models to maximize the accuracy and reliability of the inspection systems.
The Pathway to Advanced AI-Inspections
Initiating the process with traditional CV allows our solutions to deliver immediate value in capturing and consolidating data that factory teams need to facilitate and accelerate labelling for inspection model training.
The next phase involves training inspection models that can be immediately deployed due to the maturity of many manufacturing processes. Most of these processes are highly efficient meaning manufacturers are seeking solutions to find specific defects or issues that they have not been able to achieve with traditional quality testing methodologies-. Many factories have mature processes in place This sets the stage for transitioning to comprehensive AI inspection models.
Using the model training tools in our OneView software, Production or Quality team members use images marked with algorithm-applied labels (and validated with human-applied labels) to train sophisticated AI models. Factory teams then can choose to continue using a mixed approach or transition entirely to supervised AI models.
Custom Solutions for Diverse Needs
Eigen’s approach has been successfully implemented across various manufacturing applications, from enhancing defect visibility through filtering to initiating data collection with basic thermal analysis. Anomaly models serve as a safety net to guard against data drift, providing an additional layer of security.
The synergy between traditional CV and advanced AI inspections enhances the quality and efficiency of manufacturing processes. It paves the way for innovative, scalable solutions that standardize data and inspections and are flexible to meet the evolving needs of our customers.
To discuss how to take your CV-powered inspections to the next level with AI-powered, non-destructive inspection solutions, drop us a line.