Object Sorting Mechanism by Using Computer Vision

Bearing and Gear are the main cause of a poor quality and difficulty to the manufacturer. Inspection process is done on these are mostly non-automatic and very time consuming. To reduce error on identifying bearing and gear defects requires more automatic and accurate inspection process. By considering these defects, the research improve a bearing and gear defect recognizer, which uses computer vision for the defect detection. The recognizer identifies the bearing and gear defects within economical cost. In this firstly, the camera capture the digital images by image acquisition device and converts the image to binary image by local threshold techniques. Later, the outputs of the processed image are the area of the faulty portion and compute the possible defective and non –defective bearing and gear as an output.