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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shih, F.Y. Yang, C.-H.T. |
| Copyright Year | 1993 |
| Description | Author affiliation: Dept. of Comput. & Inf. Sci., New Jersey Inst. of Technol., Newark, NJ, USA (Shih, F.Y.; Yang, C.-H.T.) |
| Abstract | A distance transformation converts a digital binary image that consists of object (foreground) and non-object (background) pixels into a gray-scale image in which each object pixel has a value corresponding to the minimum distance from the background by a distance function. Due to its nonlinearity, the global operation of Euclidean distance transformation (EDT) is difficult to decompose into small neighborhood operations. Two efficient algorithms on EDT are presented, using integers of squared Euclidean distances in which the global computations can be equivalent to local 3/spl times/3 neighborhood operations. The first algorithm requires only a limited number of iterations on the chain propagation. The second algorithm can avoid iterations, and simply requires two scans of the image. The complexity of both algorithms is only linearly proportional to image size.< |
| Starting Page | 607 |
| Ending Page | 608 |
| File Size | 162543 |
| Page Count | 2 |
| File Format | |
| ISBN | 081863880X |
| ISSN | 10636919 |
| DOI | 10.1109/CVPR.1993.341063 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1993-06-15 |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Euclidean distance Iterative algorithms Pixel Computer vision Morphology Laboratories Image converters Gray-scale Rotation measurement Image analysis |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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