Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 353-368 |
| Journal | Image and Vision Computing |
| Volume | 15 |
| DOIs | |
| Publication status | Published - 1997 |
Fingerprint
Cite this
}
2D Feature Detection via Local Energy. / Robbins, B.; Owens, Robyn.
In: Image and Vision Computing, Vol. 15, 1997, p. 353-368.Research output: Contribution to journal › Article
TY - JOUR
T1 - 2D Feature Detection via Local Energy
AU - Robbins, B.
AU - Owens, Robyn
PY - 1997
Y1 - 1997
N2 - Accurate detection and localisation of two-dimensional (2D) image features (or 'key-points') is important for vision tasks such as structure from motion, stereo matching and line labelling. Despite this interest, no one has produced an adequate definition of 2D image features that encompasses the variety of features that should be included under this banner. In this paper, we present a new method for the detection of 2D image features that relies upon maximal 2D order in the phase domain of the image signal. Points of maximal phase congruency correspond to all the different types of 2D features detected by other schemes, including grey-level corners, line terminations, and a variety of junctions. An assessment of our implementation's performance is provided, in terms of its robustness, accuracy of detection and localisation of 2D image features.
AB - Accurate detection and localisation of two-dimensional (2D) image features (or 'key-points') is important for vision tasks such as structure from motion, stereo matching and line labelling. Despite this interest, no one has produced an adequate definition of 2D image features that encompasses the variety of features that should be included under this banner. In this paper, we present a new method for the detection of 2D image features that relies upon maximal 2D order in the phase domain of the image signal. Points of maximal phase congruency correspond to all the different types of 2D features detected by other schemes, including grey-level corners, line terminations, and a variety of junctions. An assessment of our implementation's performance is provided, in terms of its robustness, accuracy of detection and localisation of 2D image features.
U2 - 10.1016/S0262-8856(96)01137-7
DO - 10.1016/S0262-8856(96)01137-7
M3 - Article
VL - 15
SP - 353
EP - 368
JO - Image and Vision Computing Journal
JF - Image and Vision Computing Journal
SN - 0262-8856
ER -