Name
Abstract | ||
|---|---|---|
The Hough transform is a relatively simple and robust method for detection of economically parameterized geometric features via accumulators in the discretized parameter space. Several methods for detecting circular structure have been proposed, with centers of circles often detected as intersections of normals to the tangents of curves. We modify the transform to detect general rotationally invariant, continuously-valued image features, based on gradient measurements independent of radii. This method is robust to uncertainties in surfaces which are poorly modeled by standard stochastic models. Examples of application of the transform are from paleontological classification of digitized fossil molar surfaces |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1109/ICIP.1994.413248 | Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference |
Keywords | Field | DocType |
Hough transforms,archaeology,feature extraction,image classification,Hough transform,accumulators,centers,circles,circular structure detection,continuously-valued image features,curves,digitized fossil molar surfaces,discretized parameter space,geometric feature extraction,geometric features detection,gradient measurements,image analysis,intersections,normals,paleontological classification,robust method,rotationally invariant surface features,tangents | Computer vision,Discretization,Feature detection (computer vision),Pattern recognition,Computer science,Feature (computer vision),Hough transform,Feature extraction,Tangent,Invariant (mathematics),Artificial intelligence,Contextual image classification | Conference |
Volume | ISBN | Citations |
1 | 0-8186-6952-7 | 2 |
PageRank | References | Authors |
0.43 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mike Hoffelder | 1 | 2 | 0.43 |
| Sauer, K. | 2 | 2 | 0.43 |
| J. Keith Rigby Jr. | 3 | 2 | 0.43 |