Compact Camera Module(CCM) is widely used in PDA, Celluar phone and PC web camera. With the greatly increasing use for mobile applications, there has been a considerable demands for high speed production of CCM. The major burden of production of CCM is assembly of lens module onto CCD or CMOS packaged circuit board. After module is assembled, the CCM is inspected. In this paper, we developed the image capture board for CCM and the imaging processing algorithm to inspect the defects in captured image of assembled CCMO. The performances of the developed inspection system and its algorithm are tested on samples of 10000 CCMs. Experimental results reveal that the proposed system can focus the lens of CCM within 5s and we can recognize various types of defect of CCM modules with good accuracy and high speed.
In this paper, we present a practical approach to automatic visual inspection of SMT PCBs. There are thousands of chip components mounted on the notebook SMT PCB. The images of those chip components could not be exactly same due to the variance of shift, orientation, scale, and illumination condition. Even so, we could not memorize all kinds of inspection reference values for the different conditions. Most of inspection algorithms with fixed window template such as template matching, Fourier analysis, OCR, etc., do not show good performance for images with shifted, oriented, scaled, and variable illumination conditions. We propose a practical automatic inspection method of SMT rectangular chips; correcting the image variance of shift, orientation, and scale with practical speed, and updating the decision reference values in the inspection process. The performance of the proposed method is tested on numerous samples of rectangular chips on SMT PCB.
12 This paper deals with an image sensor system and its position estimation algorithm for autonomous duct cleaning and inspection mobile robots. For the real application, a hierarchical control structure that consists of robot motion controller and image sensor system is designed considering the efficient and autonomous motion behaviors in narrow space such as air ducts. The sensor's system consists of a CCD camera and two laser sources to generate slit beams. The image of the structured lights is used for calculating the geometric parameters of the air ducts which are usually designed with a rectangular section. With the acquired 3D information about the environment, the mobile robot with two differential driving wheels is able to autonomously navigates along the duct path without any human intervention. For real time navigation, the relative position estimation of the robot are performed from 3D image reconstructed by the sensor system. The calibration and image processing methods used for the sensor system are presented with the experimental data. The experimental results show the possibility of the sensor based navigation which is important for effective duct cleaning by small mobile robots.
12 Ever since surface-mounting technology for printed circuit board (PCB) assembly processes has been developed, electrical products continuously tend toward the miniaturization of components, with denser packing of its boards. With the increasing necessity for reliable PCB product, there has been a considerable demand for high speed, high precision vision system to place the electric parts on PCB automatically. To recognize the electric parts with high accuracy and reliability, illumination condition is instrumental to acquisition of part images. In this paper, a versatile lighting is developed which utilizes three different types of illuminating methods: direct, indirect, and back-light illumination.
The ball grid array (BGA) chip is widely used in high density printed circuit board (PCB). However, inspection of defects in the solder joints is difficult by visual or a normal x-ray imaging method, because unlike conventional packages, solder joints of the BGA are located underneath its own package and ball type leads. Therefore, x-ray digital tomosynthesis (DT), which form a cross-sectional image of 3D objects, is needed to image and inspect the solder joints of BGA. In this paper, we propose a series of algorithms for inspecting the solder joints of BGA by using x-ray cross-sectional images that are acquired from the developed DT system. BGA solder joints are examined to check the alignment between the chip and pad on a PCB, bridge, adequate solder volume. The volume of the solder joint is represented by a gray level in the x-ray images: thus solder joints can be examined by use of the gray-level profiles of each joint. To inspect and classify various defects, pattern classification method using a learning vector quantization neural network and a look up table is proposed. The clusters into which a gray-level profile is classified are generated by the learning process of the network by using a number of sampled gray-level profiles. A series of these developed algorithms for inspecting and classifying defects were tested on a number of BGA solder joints. The experimental results show that the proposed method yields satisfactory solutions for inspection based on x-ray cross-sectional images.
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