Flaw detection method and apparatus

Abstract

The invention provides a defect detection method and a defect detection device. In the defect detection device a camera part obtains a checked image of a substrate, and an edge extracting filter extracts the edge by extracting binary from the checked image. Then based on a concentration curve chart of a graph with edge removal from the checked image, the method calculates a checking threshold forgenerating a checking processed image which enable the checked image binarization. In the contentration curve chart, because the edge is removed, a pixel frequency is ''0'' at a concentration belt between a concentration distribution corresponding to a wiring diagram and a concentration distribution corresponding to a substrate body, thereby definitely separating two concentration distributions. Thus the invention can employ the maximum concentration of the concentration distribution corresponding to the substrate body as a checking threshold, and high precisely calculate the checking threshold.

Description

technical field [0001] The present invention relates to techniques for detecting defects in geometric patterns on substrates. Background technique [0002] In the field of inspecting geometrical patterns such as wiring formed on printed wiring boards, semiconductor substrates, glass substrates, etc. (hereinafter referred to as "substrates"), various inspection methods have conventionally been used. JP-A-5-340731 (Document 1) and JP-A-8-220013 (Document 2) disclose a detection method. For example, a multi-grayscale image of a substrate on which a wiring pattern is formed is obtained, and the The binary image obtained by binarizing the multi-gradation image is compared with a binary image of a normal substrate prepared in advance to detect defects. [0003] In the inspection device of Document 1, the multi-grayscale digital image of the board obtained by a CCD (Charge Coupled Device) camera and subjected to AD conversion is binarized according to an appropriately determined a...

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Problems solved by technology

As a result, defects such as short circuits cannot be detected.

[0007] In the device of Document 2, when there is much noise in the base material portion or the vicinity of the edge of the wiring pattern in the multivalued digital image is unstable, the difference between the peak of the concentration distribution of the base material portion and the peak of the concentration distribution of the pattern portion The frequency of the trough part between increases, so the binarization threshold for inspection may converge with a larger value

Therefore, the improvement of defect detection accuracy is limited

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