Method of edge detection in optical images using neural network classifier
US5311600A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Sep 29, 1992 |
| Grant date | May 10, 1994 |
| Priority date | — |
| Expiry date | Sep 29, 2012 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An image processor employing a camera, frame grabber and a new algorithm for detecting straight edges in optical images is disclosed. The algorithm is based on using a self-organizing unsupervised neural network learning to classify pixels on a digitized image and then extract the corresponding line parameters. The image processor is demonstrated on the specific application of edge detection for linewidth measurement in semiconductor lithography. The results are compared to results obtained by a standard straight edge detector based on the Radon transform; good consistency is observed; however, superior speed is achieved for the proposed image processor. The results obtained by the proposed approach are also shown to be in agreement with Scanning Electron Microscope (SEM) measurements, which is known to have excellent accuracy but is an invasive measurement instrument. The method can thus be used for on-line measurement and control of microlithography processes and for alignment tasks as well.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.