Paper
8 October 2007 A classification and verification of real pattern defects with dust filtering in tape substrate inspection
Young Jun Roh, Cheol Woo Kim, Jung Yeol Yeom, Chang Ook Jung, Dae Hwa Jeong
Author Affiliations +
Proceedings Volume 6718, Optomechatronic Computer-Vision Systems II; 67180E (2007) https://doi.org/10.1117/12.754561
Event: International Symposium on Optomechatronic Technologies, 2007, Lausanne, Switzerland
Abstract
Tape substrate pattern of ultra-fine pitch circuit less than 10 micrometers in pattern width, is required to be inspected through high resolution optics. In the process of picking out defects at the level of the critical dimension through image processing, however, trivial blemishes formed by dust or micro particles may be detected simultaneously. This leads to unnecessary work on the part of operators reviewing and verifying the additional detected points. To maximize the efficiency of the inspection process, we need to identify and classify the defect candidates whether it is a real pattern defect or simply a trivial blemish by dust. Since a real defect arising from under or over etching bears inherent features in shape and brightness, it can thus be discriminated from other trivial blemishes. In this article, we propose an image feature based defect classification method, where proper measures were obtained from a series of image analysis with FFT. Based on the data collected from experiments, we devised a statistic model for classification.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Young Jun Roh, Cheol Woo Kim, Jung Yeol Yeom, Chang Ook Jung, and Dae Hwa Jeong "A classification and verification of real pattern defects with dust filtering in tape substrate inspection", Proc. SPIE 6718, Optomechatronic Computer-Vision Systems II, 67180E (8 October 2007); https://doi.org/10.1117/12.754561
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KEYWORDS
Inspection

Image processing

Image segmentation

Particles

Defect detection

Image classification

Statistical modeling

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