Use a video source (such as a webcam or video file) to detect anomalies in the objects moving on a conveyor belt, and check for defects in color and orientation of the object.
Gain insight into the following solutions:
Computer vision applications for IoT
Inference to analyze datasets
Industrial IoT market
Learn to build and run an application with these capabilities:
❶ Detect and analyze irregularities.
❷ Monitor for color consistency and flaws.
❸ Read various kinds of bar codes.
How It Works
This application uses video input to track manufactured objects on a conveyor belt and identifies any defects in the objects. Images of defective objects are saved in unique folders depending on the type of defect.
The Intel Distribution of OpenVINO toolkit includes the following OpenCV functions that help detect object flaws.
inRange: Creates a mask, analyzes the color of an object, detects color anomalies, and identifies the defective area.
findContours: Identifies the contours and orientation of the object from the morphological opening and closing of the mask.
cvtColor: Transforms the image from BGR (blue, green, red) format to grayscale to detect and monitor cracks.
flow diagram showing how the store traffic monitor application works