Name
Abstract | ||
|---|---|---|
In this paper we present a new stochastic model for pixels in an edge-enhanced image. The model is robust because it allows for the possibilities of false and multiple edges, and may be efficiently estimated using an expectation-maximization technique with a minimum description length metric. The direct applicability of the model for the sequential edge linking algorithm is investigated and shown to improve edge detection for low signal-to-noise ratio cases. (C) 2004 SPIE and IST. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1117/1.1790507 | JOURNAL OF ELECTRONIC IMAGING |
Keywords | Field | DocType |
gaussian mixture model,signal to noise ratio,edge detection,edge enhancement | Canny edge detector,Pattern recognition,Computer science,Edge detection,Minimum description length,Signal-to-noise ratio,Artificial intelligence,Stochastic modelling,Pixel,Multiple edges,Mixture model | Journal |
Volume | Issue | ISSN |
13 | 4 | 1017-9909 |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gregory W. Cook | 1 | 37 | 5.46 |
| Edward J. Delp | 2 | 2321 | 351.37 |