Defect detection of electronic devices by single stereo vision

Akira Kusano; Takashi Watanabe; Takuma Funahashi; Takayuki Fujiwara; Hiroyasu Koshimizu

doi:10.1117/12.890925

12 July 2011 Defect detection of electronic devices by single stereo vision

Akira Kusano, Takashi Watanabe, Takuma Funahashi, Takayuki Fujiwara, Hiroyasu Koshimizu

Proceedings Volume 8000, Tenth International Conference on Quality Control by Artificial Vision; 800004 (2011) https://doi.org/10.1117/12.890925
Event: 10th International Conference on Quality Control by Artificial Vision, 2011, Saint-Etienne, France

Abstract

It is very important to guarantee the quality of the industrial products by means of visual inspection. In order to reduce the soldering defect with terminal deformation and terminal burr in the manufacturing process, this paper proposes a 3D visual inspection system based on a stereo vision with single camera. It is technically noted that the base line of this single camera stereo was precisely calibrated by the image processing procedure. Also to extract the measuring point coordinates for computing disparity; the error is reduced with original algorithm. Comparing its performance with that of human inspection using industrial microscope, the proposed 3D inspection could be an alternative in precision and in processing cost. Since the practical specification in 3D precision is less than 0.02 mm and the experimental performance was around the same, it was demonstrated by the proposed system that the soldering defect with terminal deformation and terminal burr in inspection, especially in 3D inspection, was decreased. In order to realize the inline inspection, this paper will suggest how the human inspection of the products could be modeled and be implemented by the computer system especially in manufacturing process.

Citation Download Citation

Akira Kusano, Takashi Watanabe, Takuma Funahashi, Takayuki Fujiwara, and Hiroyasu Koshimizu "Defect detection of electronic devices by single stereo vision", Proc. SPIE 8000, Tenth International Conference on Quality Control by Artificial Vision, 800004 (12 July 2011); https://doi.org/10.1117/12.890925

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