Journal of Engineering and Applied Sciences
5955 - 5961
Chun, K., K. Lee, D. Lee and B. Kim, 2018. Analysis of AOI system parameters for FOG image enhancement. Adv. Sci. Lett., 24: 4926-4930.CrossRef | Direct Link |
Chung, M.J., S.Y. Son and Y.H. Yee, 2010. High precision XY stage for production and inspection equipment of organic light-emitting diode display. Adv. Appl. Mech. Eng. Technol., 1: 19-34.Direct Link |
Dong, X.F., Z.Y. Han, S.Y. Liao and X.X. Yi, 2014. Study on semiconductor surface defect detection based on machine Vision. Metrolo. Meas. Technol., 5: 22-24.Direct Link |
Jing, D., X. Peng, Y. Zhijia and M. Ji-Kai, 2015. Micron defect inspection for wafer surface. Comput. Eng. Des., 36: 1671-1675.
Kim, B., D. Lee, K. Lee and K. Chun, 2017. DIC consistent calibration for indentation mark verification in ACF images. J. Eng. Appl. Sci., 12: 6666-6671.CrossRef | Direct Link |
Lee, D., K. Lee, K. Chun and B. Kim, 2018. High definition image acquisition for automatic optical inspection using light sources characteristics. Adv. Sci. Lett., 24: 4936-4941.Direct Link |
Martinez, S.S., J.G. Ortega, J.G. Garcia, A.S. Garcia and E.E. Estevez, 2013. An industrial vision system for surface quality inspection of transparent parts. Intl. J. Adv. Manuf. Technol., 68: 1123-1136.CrossRef | Direct Link |
Tao, X., Z.T. Zhang, F. Zhang, Y. Shi and D. Xu, 2014. Development of detection techniques of surface defects for large aperture optical elements based on machine vision. Proceedings of the 33rd Chinese Conference on Control, July 28-30, 2014, IEEE, Nanjing, China, pp: 2935-2940.
Yubao, L., 2013. Research of surface defects detection algorithm based on machine vision. Master Thesis, Central South University, Changsha, China.