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Edge and Corner Detection by Photometric Quasi-Invariants
April 2005 (vol. 27 no. 4)
pp. 625-630
ASCII Text
x 
 
Joost van de Weijer, Theo Gevers, Jan-Mark Geusebroek, "Edge and Corner Detection by Photometric Quasi-Invariants," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 4, pp. 625-630, April, 2005.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2005.75,
author = {Joost van de Weijer and Theo Gevers and Jan-Mark Geusebroek},
title = {Edge and Corner Detection by Photometric Quasi-Invariants},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {27},
number = {4},
issn = {0162-8828},
year = {2005},
pages = {625-630},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2005.75},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Edge and Corner Detection by Photometric Quasi-Invariants
IS - 4
SN - 0162-8828
SP625
EP630
EPD - 625-630
A1 - Joost van de Weijer,
A1 - Theo Gevers,
A1 - Jan-Mark Geusebroek,
PY - 2005
KW - Edge and feature detection
KW - invariants
KW - color.
VL - 27
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Feature detection is used in many computer vision applications such as image segmentation, object recognition, and image retrieval. For these applications, robustness with respect to shadows, shading, and specularities is desired. Features based on derivatives of photometric invariants, which we will call full invariants, provide the desired robustness. However, because computation of photometric invariants involves nonlinear transformations, these features are unstable and, therefore, impractical for many applications. We propose a new class of derivatives which we refer to as quasi-invariants. These quasi-invariants are derivatives which share with full photometric invariants the property that they are insensitive for certain photometric edges, such as shadows or specular edges, but without the inherent instabilities of full photometric invariants. Experiments show that the quasi-invariant derivatives are less sensitive to noise and introduce less edge displacement than full invariant derivatives. Moreover, quasi-invariants significantly outperform the full invariant derivatives in terms of discriminative power.

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Index Terms:
Edge and feature detection, invariants, color.
Citation:
Joost van de Weijer, Theo Gevers, Jan-Mark Geusebroek, "Edge and Corner Detection by Photometric Quasi-Invariants," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 4, pp. 625-630, April 2005, doi:10.1109/TPAMI.2005.75
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