Robust regression methods for computer vision: a review
International Journal of Computer Vision
Edge detection in range images based on scan line approximation
Computer Vision and Image Understanding
Cooperative Robust Estimation Using Layers of Support
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Edge Detection in Range Images of Piled Box-like Objects
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
An Approach to Outlier Detection Based on Bayesian Probabilistic Model
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
| Hi-index | 0.00 |
This paper proposes a robust multiresolution approach to detecting the structure of a noisy range image. It is assumed that the original image, consisting of planar and quadratic surfaces, is corrupted by heavy noise composed of Gaussian background noise and impulse noise. A basic principle of our approach is the exploitation of the structure of scan lines for detecting the image structure. Thus, the main part of our algorithm is essentially one-dimensional, allowing a significant decrease in computational complexity. A new curve recognition technique based on multiresolution hypothesis testing is suggested. This technique allows us to take into account domain knowledge and to improve the efficiency of the method. Finally, a procedure for detection, recognition, and reconstruction of surface patches is introduced.