The circle-end-face centering device which is in the base of image processing accomplishes the center of the cylinders end face by digital image processing. Through edge extraction and doing the matching in the calculation of the least square method, the coordinate of the central of the circle can be calculated. At last, the drill will be moved to the central of the circle and do the punching by the actuator. This equipment is in the high accuracy and speed compared with the traditional way and the concentric circle laser of marking with the center. Meanwhile, the actuator consists of the programmable logic controller, touch panel and servo drivers which is in the high stability and accuracy. Certainly it is easy to be controlled by the method.

To solve the problem of chip damage caused by the using the wrong type of vacuum nozzle during the packaging of semiconductor chips. A recognition system of vacuum nozzle based on machine vision was proposed. In this research, 29 kinds of lifting nozzles are selected as test samples. The backlight intensity of two lifting nozzle images (one strong and one weak separately) is collected at the first beginning. Then, the Blob analysis method is using to analyze the weak backlighting image. The area of the lifting nozzle and the minimum outer rectangular feature can be obtained subsequently. To identify the shape of the liftin nozzle (round or square), the area ratio is calculated. At the same time, the minimum outer rectangular of the lifting nozzle is selected as the reference rectangle. Then, construct the measurement rectangle. The 2-dimensional size of the lifting nozzle is measured as well. Meanwhile, for the strong backlight image, the average value of the grayscale which located within the minimum outer rectangle is calculated. Therefore, the color (black, white, or beige) of the nozzle can be identified. Finally, the sample data is saved to the database as the sample database. During the recognition process, the shape, color, and size of the lifting nozzle being analyzing are using as the parameter to realize the condition inquire. The experimental results show that the recognition accuracy of this method is 98.85%, and the recognition time of one nozzle is around 1 second, which meets the requirements of practical application.