IEEE Transactions on Pattern Analysis and Machine Intelligence
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental reconstruction of 3D scenes from multiple, complex images
Artificial Intelligence
Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
Detecting buildings in aerial images
Computer Vision, Graphics, and Image Processing
A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
Using Perceptual Organization to Extract 3D Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection and Linear Feature Extraction Using a 2-D Random Field Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
A Bayesian Approach to Dynamic Contours Through Stochastic Sampling and Simulated Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hough transform for feature detection in panoramic images
Pattern Recognition Letters
An algorithm for automatic detection of runways in aerial images
Machine Graphics & Vision International Journal
Panoramic stereo reconstruction using non-SVP optics
Computer Vision and Image Understanding
A straight line detection using principal component analysis
Pattern Recognition Letters
Classified road detection from satellite images based on perceptual organization
International Journal of Remote Sensing
Circular Sub-window Multi-Step GPI Method in Seam Tracking of Welding Robot Based on 3D Vision
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part II
Extraction of Line Feature in Binary Images
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Panoramic stereo reconstruction using non-SVP optics
Computer Vision and Image Understanding
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A straight-line extractor that produces line descriptions from aerial images is described. The input to the line extractor is in the form of an edge image, where the contrast and direction of each edge pixel is specified. The system scans the edge image left to right and top to bottom and assigns a line label for each scanned edge pixel, thereby generating a label image. At the end of this process, each edge pixel has a line label associated with it, and edge pixels that belong to the same line will be assigned the same line label. In addition, with each line label, a record that stores the end points, the average contrast, and the pixel support of the line is generated. The label image is used as a spatial index to further link fragmented lines. The authors also describe techniques for eliminating many of the physically insignificant lines, given that the domain of interpretation is aerial images dominated by man-made objects.