Data processing: measuring – calibrating – or testing – Measurement system
Reexamination Certificate
2001-06-25
2004-01-06
Barlow, John (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system
C382S147000
Reexamination Certificate
active
06675120
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates to optical inspection systems of electronic assemblies, and more particularly to color optical inspection of devices present on a printed circuit board.
Printed circuit boards (PCB) are typically populated by a number of discrete electrical devices, such as capacitors, inductors, resistors, as well as Integrated Circuits (ICs), all of which are mounted on the PCB surface. The process of assembling devices on a PCB is typically highly automated. In most conventional PCB assembly systems, a computer aided design (CAD) tool is used to identify the mounting position of each device, as well as the connections between each device's pins and the electrically conductive traces present on the PCB surface. However, even though highly automated, PCB assembly processes are prone to defects. Therefore, following assembly, each PCB is preferably inspected for possible defects.
Defects on a PCB may be of different types and arise from varying sources. For example, PCB defects may be caused by missing devices, misaligned or tilted devices, wrong devices, soldering defects, etc.
PCB defect detection systems are generally based on one of the following three broad categories: x-ray, laser scanning and visual (optical) inspection systems.
In an x-ray inspection system, an x-ray beam is passed through a PCB assembly to generate an x-ray image of the PCB assembly. X-ray inspection systems, while very accurate in detecting certain classes of defects, such as solder-related defects, are not suited for detecting defects caused by certain other classes of defects, such as those arising from, e.g., misplaced devices.
Laser scanning inspection systems scan a laser beam across the surface of a PCB assembly to form a three-dimensional image of the PCB assembly. Thereafter, the three-dimensional image of the PCB assembly is compared with that of a known defect-free PCB assembly to identify certain types of possible defects. Like x-ray inspection systems, laser scanning inspection systems also have a limited defect detection capability. For example, a laser scanning inspection system typically cannot identify a defect caused by a mounted resistor which has a wrong resistance value.
Optical inspection systems can capture an image of a PCB assembly via a camera system and compare the captured image with that of a defect-free PCB assembly in order to detect possible defects. Both monochrome as well as color optical inspection systems are available and used.
Monochrome optical inspection systems can only form gray scale images of a PCB assembly. Therefore, such systems cannot capture and process any information related to color features of a PCB device. For example, monochrome optical inspection systems cannot identify the value of a discrete resistor's resistance—which is typically coded by the color of rings present on the outer surface of the resistor. Similarly, monochrome optical inspection systems are unable to match the color of a device to that of a reference device to verify, for example, that the device is mounted in its designated PCB position.
In order to rectify the problems stemming from the color-blindness of the prior art monochrome optical inspection systems, color optical inspection systems have been developed. Prior art color optical inspection systems, however, are either costly or slow when required to operate reliably, that is to operate with a certain defect detection accuracy.
Some prior art color optical inspection systems contain parallel image processing capability to thereby speed up their inspection rate. They are typically costly to purchase and maintain. Other prior art color inspection systems contain a single image processing stage and are thus less expensive than multi-stage parallel image processing systems. However, depending on the required level of defect detection accuracy, such systems require a number of execution cycles to form and compare images and thus have a relatively slower throughput.
BRIEF SUMMARY OF THE INVENTION
According to the invention, a color optical inspection system is provided which extracts only such luma and chroma spatial features as are necessary for detection of defects related to physical characteristics of the devices populating the surface of a board, such as a printed circuit board (PCB). The color optical inspection system carries out defect detection in two phases, a training phase followed by an inspection phase.
During the training phase, the color optical inspection system, with the help of an operator, extracts spatial features of each device present on each of a number of golden boards—which are known to contain no defects. The extracted spatial features of each device on the golden boards are compared against a set of established criteria to identify and select one or more spatial features to be extracted for the associated devices (associated devices are devices appearing on the same physical locations on all the PCBs, golden or otherwise) during the inspection phase. Furthermore, for similarly located devices on the golden boards, a match region whose boundaries are defined by the selected spatial feature(s) of that device is established.
During the inspection phase, the selected spatial feature(s) of each device on the PCB is extracted to determine whether it falls inside a corresponding match region. If the extracted feature(s) falls inside the corresponding match region, no defect is reported, otherwise color optical inspection system
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reports both the presence as well as the position of the defect on the PCB undergoing inspection.
In a specific embodiment, the color inspection system of the present invention includes an image acquisition system and an image feature extraction system. The image acquisition system includes, among other components, a Bayer color filter, a charge coupled device (CCD) imager, an interpolator and a gamma corrector
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. The image feature extraction system includes a color component converter and a number of spatial feature extractors.
In operation, light received from a device passes through a Bayer color filter before reaching an M×N array of CCD light sensitive pixels. The Bayer color filter contains an M×N array of red, green and blue color filters so positioned as to match the corresponding positions of the M×N array of pixels of the CCD imager, which in response generates an M×N array of digitized signals for each of the color components red, green and blue. The signals generated by the CCD imager are applied to an interpolator which performs a bilinear spatial interpolation on the applied signals and which are subsequently corrected for the gamma factor by a gamma corrector.
The gamma-corrected signals, each of which includes an array of M×N signals, are applied to a color component converter which reduces the degree of correlation of the signals applied thereto, thereby to generate a luma component and two orthogonal chroma components of the viewed device.
The luma and chroma color component signals generated by the color component converter are subsequently applied to respective spatial feature extractors which respectively extract spatial features associated with the device in view.
Depending on the values of the three spatial features of each device on the golden boards, one, two or all three spatial features of the associated device may be extracted during the inspection phase. If, during the training phase of a device, only the first spatial feature is selected for defect detection, then during the subsequent inspection phase, the second and third spatial features of the associated device are not extracted.
If, for example, an integrated circuit (IC) is in view, because only black (or gray) and white colors are typically present on its surface, the second and third spatial features of the IC—which represent its chroma components—are not extracted during the inspection phase, in accordance with the selection made during the training phase. To determine the presence or absence of a defect due
Pratt William K.
Sit Owen Y.
Allen Kenneth R.
Barlow John
Photon Dynamics, Inc.
Townsend and Townsend / and Crew LLP
Xiuqin Sun
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