01322nas a2200157   4500008004100000020002300041245004400064210004400108260003300152300001600185520081900201100001901020700001901039700001701058856008901075       2009                        eng d  a978-1-4244-5653-6 00aNonlinear registration of binary shapes0 aNonlinear registration of binary shapes  aCairo, EgyptbIEEEcNov 2009  a1101 - 11043 a<p>A novel approach is proposed to estimate the parameters of a diffeomorphism that aligns two binary images. Classical approaches usually define a cost function based on a similarity metric and then find the solution via optimization. Herein, we trace back the problem to the solution of a system of non-linear equations which directly provides the parameters of the aligning transformation. The proposed method works without any time consuming optimization step or established correspondences. The advantage of our algorithm is that it is easy to implement, less sensitive to the strength of the deformation, and robust against segmentation errors. The efficiency of the proposed approach has been demonstrated on a large synthetic dataset as well as in the context of an industrial application. ©2009 IEEE.</p>1 aNemeth, Jozsef1 aDomokos, Csaba1 aKato, Zoltan  uhttps://tisat.inf.u-szeged.hu/en/publication/nonlinear-registration-of-binary-shapes01266nas a2200109   4500008004100000245005300041210005300094260001800147300001600165520092800181856004701109       2009                        eng d00aRecovering planar homographies between 2D shapes0 aRecovering planar homographies between 2D shapes  bIEEEc2009///  a2170 - 21763 a<p>Images taken from different views of a planar object are related by planar homography. Recovering the parameters of such transformations is a fundamental problem in computer vision with various applications. This paper proposes a novel method to estimate the parameters of a homography that aligns two binary images. It is obtained by solving a system of nonlinear equations generated by integrating linearly independent functions over the domains determined by the shapes. The advantage of the proposed solution is that it is easy to implement, less sensitive to the strength of the deformation, works without established correspondences and robust against segmentation errors. The method has been tested on synthetic as well as on real images and its efficiency has been demonstrated in the context of two different applications: alignment of hip prosthesis X-ray images and matching of traffic signs. ©2009 IEEE.</p>  uhttps://tisat.inf.u-szeged.hu/en/node/1228