A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Line detection in digital pictures: a hypothesis prediction/verification pardigm
Computer Vision, Graphics, and Image Processing
On approximating polygonal curves in two and three dimensions
CVGIP: Graphical Models and Image Processing
An optimal algorithm for closest pair maintenance (extended abstract)
Proceedings of the eleventh annual symposium on Computational geometry
Inferring global perceptual contours from local features
International Journal of Computer Vision - Special issue on computer vision research at the University of Southern California
Handbook of discrete and computational geometry
Handbook of discrete and computational geometry
A Comparison of Measures for Detecting Natural Shapes in Cluttered Backgrounds
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
Computer Processing of Line-Drawing Images
ACM Computing Surveys (CSUR)
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Figure-Ground Discrimination: A Combinatorial Optimization Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding Line Segments by Stick Growing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Edge Detection: Learning and Evaluating Edge Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lineal Feature Extraction by Parallel Stick Growing
IRREGULAR '96 Proceedings of the Third International Workshop on Parallel Algorithms for Irregularly Structured Problems
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Segmentation of Multiple Salient Closed Contours from Real Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Quantitative Measures of Change based on Feature Organization: Eigenvalues and Eigenvectors
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Divide-and-conquer in multidimensional space
STOC '76 Proceedings of the eighth annual ACM symposium on Theory of computing
Stochastic completion fields: a neural model of illusory contour shape and salience
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A Survey of Polygonal Simplification Algorithms
A Survey of Polygonal Simplification Algorithms
Camera models and machine perception
Camera models and machine perception
A fast algorithm for approximating the detour of a polygonal chain
Computational Geometry: Theory and Applications
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
Digital Geometry: Geometric Methods for Digital Picture Analysis
Digital Geometry: Geometric Methods for Digital Picture Analysis
Salient Closed Boundary Extraction with Ratio Contour
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Convex Grouping Combining Boundary and Region Information
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Supervised Learning of Edges and Object Boundaries
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
A Min-Cover Approach for Finding Salient Curves
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Evaluating edge detection through boundary detection
EURASIP Journal on Applied Signal Processing
Detection and recognition of contour parts based on shape similarity
Pattern Recognition
Multiscale Categorical Object Recognition Using Contour Fragments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-scale Improves Boundary Detection in Natural Images
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Algorithm Design: Foundations, Analysis and Internet Examples
Algorithm Design: Foundations, Analysis and Internet Examples
Some theoretical challenges in digital geometry: A perspective
Discrete Applied Mathematics
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
Contour Detection and Hierarchical Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour grouping with prior models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image segmentation with ratio cut
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic target recognition by matching oriented edge pixels
IEEE Transactions on Image Processing
Hybrid image segmentation using watersheds and fast region merging
IEEE Transactions on Image Processing
Contour detection based on nonclassical receptive field inhibition
IEEE Transactions on Image Processing
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We present a simple method based on computational-geometry for extracting contours from digital images. Unlike traditional image processing methods, our proposed method first extracts a set of oriented feature points from the input images, then applies a sequence of geometric techniques, including clustering, linking, and simplification, to find contours among these points. Extensive experimental results on synthetic and natural images show that our method can effectively extract contours from both clean and noisy images. Experiments on the Berkeley Segmentation Dataset also show that our proposed computationalgeometry method can be linked with any state-of-the-art pixel-based contour extraction algorithm to remove noise and close gaps without severely dropping the contour accuracy. Moreover, contours extracted by our method have a much more compact representation than contours obtained by traditional pixel-based methods. Such a compact representation allows more efficient extraction of shape features in subsequent computer vision and pattern recognition tasks.