Open AccessMatching corners using the informative arc
Author(s) -
Kanwal Nadia,
Bostanci Erkan,
Clark Adrian F.
Publication year - 2014
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2013.0104
Subject(s) - artificial intelligence , computer science , computer vision , pattern recognition (psychology) , matching (statistics) , encoding (memory) , object (grammar) , feature (linguistics) , corner detection , binary number , feature extraction , cognitive neuroscience of visual object recognition , object detection , feature matching , image (mathematics) , mathematics , statistics , linguistics , philosophy , arithmetic
Corners are important features in images because they typically delimit the boundaries of regions or objects. For real‐time applications, it is essential that corners are detected and matched reliably and rapidly. This study presents two related descriptors which are compatible with standard corner detectors and able to be computed and matched at video rate: one encodes the entire region within a corner, whereas the other describes only the region within an object. The advantage of encoding only the region within an object is demonstrated. The noise stability of the descriptors is assessed and compared with that of the popular binary robust independent elementary feature (BRIEF) descriptor, and the matching performances of the descriptors are compared on video sequences from hand‐held cameras and the PETS2012 database. A statistical analysis shows that performance is indistinguishable from BRIEF.