Abstract
A technique for intelligent dilation of objects in an image was developed that, when compared to standard isotropic techniques, can create a better representative resultant image for subsequent morphological analysis. Individual masses in an image are forced to grow in preferential directions with varying degrees of strength according to a set of morphological parameters. These parameters are determined by applying a model based on gravitational force to determine the strength and direction of the 'attraction force' between objects. The result of this analysis is a collection of normalized dilation vectors for each object in the image, where each vector represents a potential direction for growth. Results of the application of this algorithm are shown on binary images of defect distributions on semiconductor wafers where a single defect (e.g., a scratch) can be made up of numerous, disconnected blobs.
| Original language | English |
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| Pages | 9-12 |
| Number of pages | 4 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz Duration: Sep 16 1996 → Sep 19 1996 |
Conference
| Conference | Proceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) |
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| City | Lausanne, Switz |
| Period | 09/16/96 → 09/19/96 |