Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/146305
Title: Directional feature detection and correspondence
Authors: Wang W.-H.
Hsiao F.-J.
Chen T. 
Issue Date: 2005
Citation: Wang W.-H., Hsiao F.-J., Chen T. (2005). Directional feature detection and correspondence. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3768 LNCS : 665-675. ScholarBank@NUS Repository.
Abstract: A method is proposed to detect useful directional feature points other than corner points considering that the number of corner points may not be sufficient in a scene. This is achieved by directional analysis of properties of image points by virtue of the proposed gradient operators with different direction topologies. A matching criterion is also proposed to find the initial correspondence by using the feature vectors that are acquired from the results of directional analysis. For the purpose of improving the final correspondence, four constraints are employed in the system to seek and refine the correspondence.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/146305
ISBN: 3540300406
9783540300403
ISSN: 03029743
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.