@inproceedings{4e1199999e724b5c870e0345b4482450,
title = "Recognition and classification of ultrasonic aluminum wire joint based on image morphology and C-SVM",
abstract = "Aiming at the quality inspection of ultrasonic aluminum wire joint, this paper proposes a method of ultrasonic aluminum wire joint quality identification based on PCA and C-SVM. Firstly, extracting the ultrasonic aluminum joint image from the ultrasonic welding element image by applying image morphological operations and image histogram equalization, and then reducing the dimension of the ultrasonic aluminum joint image data by applying PCA, finally identifying the quality of the joint by applying C-SVM with Gauss-RBF kernel function. Experimental results show that this method has a high accuracy.",
keywords = "Machine Vison, PCA, SVM, Ultrasonic Aluminum wire welding",
author = "Rui Wang and Long Zhili and Zhou Xing",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 18th International Conference on Electronic Packaging Technology, ICEPT 2017 ; Conference date: 16-08-2017 Through 19-08-2017",
year = "2017",
month = sep,
day = "19",
doi = "10.1109/ICEPT.2017.8046589",
language = "英语",
series = "18th International Conference on Electronic Packaging Technology, ICEPT 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "898--903",
editor = "Chenxi Wang and Yanhong Tian and Tianchun Ye",
booktitle = "18th International Conference on Electronic Packaging Technology, ICEPT 2017",
address = "美国",
}