Title :
Wafer Defects Detecting and Classifying System Based on Machine Vision
Author :
Zhen, Zeng ; Shuguang, Dai ; Ping´an, Mu
Author_Institution :
Univ. of Shanghai for Sci. & Technol., Shanghai
Abstract :
The wafer defects detecting and classifying system based on machine vision aims at inspecting macro wafer defects. After acquiring disk images using CCD, through digital images process we realized defects inspection and defects segmentation. Finally defects classification was achieved by neural networks. The experiment results prove that the proposed system features a strong background of specialty and can be applied into practice.
Keywords :
CCD image sensors; computer vision; inspection; neural nets; CCD image sensor; defects classification; defects segmentation; digital images process; disk images; machine vision; neural networks; wafer defects classifying system; wafer defects detecting system; Digital images; Image segmentation; Inspection; Instruments; Machine vision; Mirrors; Neural networks; Optical distortion; Optical fiber networks; Optical reflection; defect detection; image process; machine vision; neural network; wafer;
Conference_Titel :
Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-1136-8
Electronic_ISBN :
978-1-4244-1136-8
DOI :
10.1109/ICEMI.2007.4351196
