[IPOL discuss] [IPOL announce] new article: Fast Affine Invariant Image Matching

[announcements about the IPOL journal]

A new article is available in IPOL: http://www.ipol.im/pub/art/2018/225/

Mariano Rodríguez, Julie Delon, and Jean-Michel Morel,
Fast Affine Invariant Image Matching,
Image Processing On Line, 8 (2018), pp. 251–281.
https://doi.org/10.5201/ipol.2018.225

Abstract
Methods performing Image Matching by Affine Simulation (IMAS) attain 
affine invariance by applying a finite set of affine transforms to the 
images before comparing them with a Scale Invariant Image Matching 
(SIIM) method like SIFT or SURF. We describe here how to optimize IMAS 
methods. First, we detail an algorithm computing a minimal discrete set 
of affine transforms to be applied to each image before comparison. It 
yields a full practical affine invariance at the lowest computational 
cost. The matching complexity of current IMAS algorithms is divided by 
about 4. Our approach also associates to each image an affine invariant 
set of descriptors, which is twice smaller than the set of descriptors 
usually used in IMAS methods, and only 6.4 times larger than the set of 
similarity invariant descriptors of SIIM methods. In order to reduce the 
number of false matches, which are inherently more frequent in IMAS 
approaches than in SIIM, we introduce the notion of hyper-descriptor, 
which groups descriptors whose keypoints are spatially close. Finally, 
we also propose a matching criterion allowing each keypoint of the query 
image to be matched with several keypoints of the target image, in order 
to deal with situations where an object is repeated several times in the 
target image.



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