@inproceedings{f0277082549f404aa39896bab000fc28,
title = "Reconstructing the 3D solder paste surface model using image processing and artificial neural network",
abstract = "In general, the laser Inspection can measure accurate 3D solder paste surface model, however, it is not practical due to the high cost and low inspection speed. This paper presents the three-dimensional (3D) solder paste surface model reconstruction using the image processing and artificial neural network (ANN), and the proposed approach forms the virtual laser 3D automatic optical inspection (AOI) model. The input nodes of the ANN model consist of the image features that are captured from images of using different light sources. The output nodes are the heights of the corresponding image pixel areas. The training patterns of the proposed ANN model use the laser 3D inspection results. Meanwhile, the in-lab design and the commercial coaxial light sources with the pad and sub-area based learning architecture models are constructed and validated, and the estimated 3D surface model achieves 90% accuracy in average.",
keywords = "3D reconstruction, Artificial neural network, Machine vision, Solder paste inspection",
author = "Yang, {Fang Chung} and Kuo, {Chung Hsien} and Wing, {Jein Jong} and Yang, {Ching Kun}",
year = "2004",
doi = "10.1109/ICSMC.2004.1400799",
language = "英语",
isbn = "0780385667",
series = "Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics",
pages = "3051--3056",
booktitle = "2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004",
note = "2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 ; Conference date: 10-10-2004 Through 13-10-2004",
}