A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour sequence moments for the classification of closed planar shapes
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
Review of shape coding techniques
Image and Vision Computing
A new curve detection method: randomized Hough transform (RHT)
Pattern Recognition Letters
A probabilistic Hough transform
Pattern Recognition
Edge linking by using causal neighborhood window
Pattern Recognition Letters
Optimal Edge Detection using Expansion Matching and Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge and Line Feature Extraction Based on Covariance Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
VLSI Architecture for Real-Time Edge Linking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Processing of Line-Drawing Images
ACM Computing Surveys (CSUR)
Edge detector evaluation using empirical ROC curves
Computer Vision and Image Understanding - Special issue on empirical evaluation of computer vision algorithms
Face Recognition Using Line Edge Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection and Surface Reconstruction Using Refined Regularization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Angular Dispersion of Gradient Direction for Detecting Edge Ribbons
IEEE Transactions on Pattern Analysis and Machine Intelligence
Logical/Linear Operators for Image Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
ISCV '95 Proceedings of the International Symposium on Computer Vision
Adaptive mathematical morphology for edge linking
Information Sciences—Informatics and Computer Science: An International Journal
On the Quantitative Evaluation of Edge Detection Schemes and their Comparison with Human Performance
IEEE Transactions on Computers
Groups of Adjacent Contour Segments for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Canny Edges Using Ant Colony Optimization
CGIV '08 Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation
Real-Time Lane Departure Detection Based on Extended Edge-Linking Algorithm
ICCRD '10 Proceedings of the 2010 Second International Conference on Computer Research and Development
Edge Drawing: A Heuristic Approach to Robust Real-Time Edge Detection
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Efficient Canny Edge Detection Using a GPU
ICNC '10 Proceedings of the 2010 First International Conference on Networking and Computing
EDLines: A real-time line segment detector with a false detection control
Pattern Recognition Letters
A methodology for quantitative performance evaluation of detection algorithms
IEEE Transactions on Image Processing
Image registration by "Super-curves"
IEEE Transactions on Image Processing
Edge Grouping Combining Boundary and Region Information
IEEE Transactions on Image Processing
A Generic Shape/Texture Descriptor Over Multiscale Edge Field: 2-D Walking Ant Histogram
IEEE Transactions on Image Processing
EDCircles: A real-time circle detector with a false detection control
Pattern Recognition
Hi-index | 0.00 |
We present a novel edge segment detection algorithm that runs real-time and produces high quality edge segments, each of which is a linear pixel chain. Unlike traditional edge detectors, which work on the thresholded gradient magnitude cluster to determine edge elements, our method first spots sparse points along rows and columns called anchors, and then joins these anchors via a smart, heuristic edge tracing procedure, hence the name Edge Drawing (ED). ED produces edge maps that always consist of clean, perfectly contiguous, well-localized, one-pixel wide edges. Edge quality metrics are inherently satisfied without a further edge linking procedure. In addition, ED is also capable of outputting the result in vector form as an array of chain-wise edge segments. Experiments on a variety of images show that ED produces high quality edge maps and runs up to 10% faster than the fastest known implementation of the Canny edge detector (OpenCV's implementation).