Abstract:
Automated vision inspection is creating a revolution as it becomes a vital part of the quality monitoring process. It offers more accuracy and efficiency. Major Automatic visual inspection responsibilities include, spotting the occurrence or deficiency of objects in the image and computing the dimensions of objects to see if they converge conditions. Measurements are built on characteristic attributes of the object represented in the image. Automatic image processing systems usually classify the type of data contained in the image as edges, surfaces, and textures, or patterns.
This project aims at the development of a system for the removal of faulty product in beverage, water bottles industries. It can be self-operational in controlling, starting with bottle detection as a faulty product then pushing the products away from the conveyor to some other basket. Our project mainly deals to detect and remove the faulty products form the product line (conveyor).
This work is currently done manually in product lines in industries. This project is divided into two major portions i.e. detecting bottles on a conveyor using IR sensor and synchronize it with the movement of conveyor using the electrical circuit part that includes Raspberry Pi microcontrollers and once the IR sensor detects bottle on conveyor it gives the signal to Raspberry Pi and Real time image is captured.
Another part is the camera for image capturing and of course Raspberry Pi for doing image processing with OpenCV libraries. Raspberry Pi is being used for image processing and sending commands to the mechanical parts to work accordingly. The camera takes the real-time image of bottles and send it to Raspberry Pi where it is matched with predefined data for template matching.
This project covers three major inspections task that are, bottle cap detection (either it is properly locked or not), logo detection (either bottle has a logo or not) and 3rd is level checking of liquid inside the bottle (either it is filled to a specific level or not).
