A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A computational approach for corner and vertex detection
International Journal of Computer Vision
Algorithms for Graphics and Imag
Algorithms for Graphics and Imag
Correction for the Dislocation of Curved Surfaces Caused by the PSF in 2D and 3D CT Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Provably correct edgel linking and subpixel boundary reconstruction
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Topologically correct image segmentation using alpha shapes
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
Computer Vision and Image Understanding
| Hi-index | 0.00 |
Image analysis attempts to perceive properties of the continuous real world by means of digital algorithms. Since discretization discards an infinite amount of information, it is difficult to predict if and when digital methods will produce reliable results. This paper reviews theories which establish explicit connections between the continuous and digital domains (such as Shannon's sampling theorem and a recent geometric sampling theorem) and describes some of their consequences for image analysis. Although many problems are still open, we can already conclude that adherence to these theories leads to significantly more stable and accurate algorithms.