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Lie group method: A new approach to image matching with arbitrary orientations
Author(s) -
Ying Shihui,
Qiao Hong
Publication year - 2010
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.20244
Subject(s) - matching (statistics) , group (periodic table) , image (mathematics) , lie group , set (abstract data type) , gradient descent , point (geometry) , face (sociological concept) , computer science , artificial intelligence , method of steepest descent , point set registration , function (biology) , algorithm , mathematics , computer vision , mathematical optimization , geometry , physics , social science , statistics , evolutionary biology , sociology , artificial neural network , biology , programming language , quantum mechanics
In this article, we develop a new method for image matching of any two images with arbitrary orientations. The idea comes from the workpiece localization in machining industry. We first describe an image as a 3D point set other than the common 2D function f ( x, y ), then, making the sets corresponding to the compared images form solid surfaces, we equivalently translate the matching problem into an optimization problem on the Lie group SE (3). Through developing a kind of steepest descent algorithms on a general Lie group, we present an practical algorithm for matching problem. Simulations of eye detection and face detection are presented to show the feasibility and efficiency of the proposed algorithm. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 245–252, 2010.