Title
A Robust Edge-Based Corner Detector (Ebcd)
Abstract
This paper presents a novel and robust edge-based corner detector (EBCD) which finds corners that are considered stable interest points in the framework of 2D object recognition especially for robot navigation. Using the EBCD, the corners are defined as intersection points of non-collinear straight image edges. The straight edge detector plus the corner detector will localize the corner positions. The detected corners have special features which are their angles and their sides length ratios. These features are invariant parameters which make the corners perfect for 2D object recognition. In addition, these corners are shown to be very robust against various image transformations like image scaling, rotation, translation and viewpoint illumination changes. Some updates are applied on the linking edge step in order to extract edges and their intersections that in turn construct the searched corners. Experiments conducted on synthetic and real images show that the proposed EBCD is able to achieve a very good performance in terms of accuracy, stability and especially computational efficiency in comparison with existing algorithms on interest points.
Year
DOI
Venue
2014
10.1142/S0219467814500181
INTERNATIONAL JOURNAL OF IMAGE AND GRAPHICS
Keywords
Field
DocType
Corners, image transformations, edge detector, straight edge, 2D object recognition
Computer vision,Edge detector,Invariant (mathematics),Artificial intelligence,Real image,Robot,Mathematics,Image scaling,Cognitive neuroscience of visual object recognition,Corner detector
Journal
Volume
Issue
ISSN
14
4
0219-4678
Citations 
PageRank 
References 
3
0.46
15
Authors
4
Name
Order
Citations
PageRank
Rabih Al Nachar1122.70
Elie Inaty23411.97
Patrick J. Bonnin371.95
Y. Alayli4174.07