Title :
A fractal dimension feature extraction technique for detecting flaws in silicon wafers
Author :
Stubbendieck, Gregg T. ; Oldham, William J B
Author_Institution :
Dept. of Comput. Sci., Texas Tech. Univ., Lubbock, TX, USA
Abstract :
The authors present a feature extraction method for detecting flaws in silicon wafers based on the idea of fractal dimension. They begin by discussing why fractal dimension is a good way to model wafer surface images. They then describe how to calculate the fractal dimension of a computer image of a wafer and how the results of such a calculation can be used for fault detection and image segmentation. The results of the application of this process to some wafer images are included
Keywords :
automatic optical inspection; feature extraction; flaw detection; fractals; image segmentation; integrated circuit testing; quality control; semiconductor technology; computer image; fault detection; feature extraction; fractal dimension; image segmentation; silicon wafers; wafer surface images; Data mining; Feature extraction; Fractals; Humans; Image segmentation; Inspection; Neural networks; Pattern recognition; Quality control; Silicon;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.227067
