An Operator Which Locates Edges in Digitized Pictures
Journal of the ACM (JACM)
A Local Visual Operator Which Recognizes Edges and Lines
Journal of the ACM (JACM)
Edge and Curve Detection for Visual Scene Analysis
IEEE Transactions on Computers
Edge and Curve Detection: Further Experiments
IEEE Transactions on Computers
A Quantitative Study of the Orientation Bias of Some Edge Detector Schemes
IEEE Transactions on Computers
Image segmentation evaluation: A survey of unsupervised methods
Computer Vision and Image Understanding
Fuzzy edge detection for omnidirectional images
Fuzzy Sets and Systems
Dimensionality in image analysis
Journal of Visual Communication and Image Representation
A gravitational approach to edge detection based on triangular norms
Pattern Recognition
Novel statistical approaches to the quantitative combination of multiple edge detectors
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
Fast communication: Analysis and improvement of SUSAN algorithm
Signal Processing
Edge Drawing: A combined real-time edge and segment detector
Journal of Visual Communication and Image Representation
Quantitative error measures for edge detection
Pattern Recognition
| Hi-index | 14.98 |
A technique for the quantitative evaluation of edge detection schemes is presented. It is used to assess the performance of three such schemes using a specially-generated set of images containing noise. The ability of human subjects to distinguish the edges in the presence of noise is also measured and compared with that of the edge detection schemes. The edge detection schemes are used on a high-resolution satellite photograph with varying degrees of noise added in order to relate the quantitative comparison to real-life imagery.