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Reconstruction of convex sets from noisy support line measurements
| Content Provider | Semantic Scholar |
|---|---|
| Author | Prince, Jerry L. Willsky, Alan S. Systems, Decision |
| Copyright Year | 1987 |
| Abstract | ABSTRACr: In many applications, measurements of the arises simply because it is impossible to support lines of a two dimensional set are precisely determine the position of the support available. From such measurements, the convex lines from (noisy) measured projections. We hull of the set may be reconstructed. If, show that a collection of noisy support line however, the measurements are noisy, then the measurements may be inconsistent with any set in set of measurements, taken together, may not the plane, and describe algorithms that exploit correspond to any set in the plane - they are the fundamental constraint that is revealed. We inconsistent. This paper describes the also indicate how prior information concerning consistency conditions for support line object shape may be included in the algorithms. measurements when the angles of the lines are precisely known, but the lateral displacements are degraded by noise. We propose three simple 2.0 DISCEE SUPPORT LINE CONSTIAIITS algorithms for obtaining consistent support line estimates based on ML and MAP estimation The support line at angle 0 for the closed principles, and show examples of the performance and bounded (2-d) set S is given by (see Figure of these algorithms. 1) |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://dspace.mit.edu/bitstream/handle/1721.1/2993/P-1667-18482284.pdf?sequence=1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
