a new algorithm for distorted fingerprints matching based on normalized fuzzy similarity measure coping with nonlinear distortions in fingerprint matching is a challenging task this paper proposes a novel algorithm normalized fuzzy similarity measure nfsm to deal with the nonlinear distortions the proposed algorithm has two main steps first the template and input fingerprints were aligned in this process the local topological structure matching was introduced to improve the robustness of global alignment second the method nfsm was introduced to compute the similarity between the template and input fingerprints the proposed algorithm was evaluated on fingerprints databases of fvc2004 experimental results confirm that nfsm is a reliable and effective algorithm for fingerprint matching with nonliner distortions the algorithm gives considerably higher matching scores compared to conventional matching algorithms for the deformed fingerprints

dense registration of fingerprints abstract dense registration of different impressions of the same finger is beneficial to various fingerprint matching methods this is a challenging problem due to elastic distortion of finger skin and sparsity of distinctive features namely minutiae in fingerprints most existing fingerprint registration algorithms produce only correspondences between minutiae which are not sufficient for dense registration of fingerprints in this paper we proposed a novel dense fingerprint registration algorithm which consists of a composite initial registration step and a dual resolution block based registration step the dual resolution block based registration is approached in an energy minimization framework which consists of local search energy function construction and global optimization in local search step a candidate set of transformations of every input image block are found using image correlation w r t the corresponding reference image block in energy function construction two factors are considered 1 the similarity between the transformed input block and the corresponding reference block and 2 the compatibility between transformations of neighboring input blocks in global optimization a region growing style algorithm is proposed to minimize the energy function experimental results on three databases containing many distorted fingerprints namely fvc2004 db1 tsinghua distorted fingerprint database and nist sd27 latent fingerprint database show that the proposed algorithm not only produces more accurate registration results but also improves the matching performance by fusion of minutiae matching and image correlation

fingerprint image postprocessing a combined statistical and structural approach abstract for complex patterns such as fingerprints it is difficult to describe the dactylotype by using a set of feature vectors as well as to construct and parse all of the individual fingerprint pattern with a syntactical approach in this paper which is different from the conventional methods we present an approach in which the statistical and structural approaches are combined to represent the fingerprint false minutia patterns based on the proposed approach a fingerprint image postprocessing algorithm is developed to eliminate the false minutiae in fingerprint images because a global minutia relation is considered on the whole image experimental results demonstrate the advantages of the combined approach

a performance evaluation of local descriptors in this paper we compare the performance of descriptors computed for local interest regions as for example extracted by the harris affine detector mikolajczyk k and schmid c 2004 many different descriptors have been proposed in the literature it is unclear which descriptors are more appropriate and how their performance depends on the interest region detector the descriptors should be distinctive and at the same time robust to changes in viewing conditions as well as to errors of the detector our evaluation uses as criterion recall with respect to precision and is carried out for different image transformations we compare shape context belongie s et al april 2002 steerable filters freeman w and adelson e setp 1991 pca sift ke y and sukthankar r 2004 differential invariants koenderink j and van doorn a 1987 spin images lazebnik s et al 2003 sift lowe d g 1999 complex filters schaffalitzky f and zisserman a 2002 moment invariants van gool l et al 1996 and cross correlation for different types of interest regions we also propose an extension of the sift descriptor and show that it outperforms the original method furthermore we observe that the ranking of the descriptors is mostly independent of the interest region detector and that the sift based descriptors perform best moments and steerable filters show the best performance among the low dimensional descriptors

fingerprint matching by thin plate spline modelling of elastic deformations this paper presents a novel minutiae matching method that describes elastic distortions in fingerprints by means of a thin plate spline model which is estimated using a local and a global matching stage after registration of the fingerprints according to the estimated model the number of matching minutiae can be counted using very tight matching thresholds for deformed fingerprints the algorithm gives considerably higher matching scores compared to rigid matching algorithms while only taking 100 ms on a 1 ghz p iii machine furthermore it is shown that the observed deformations are different from those described by theoretical models proposed in the literature

combining minutiae descriptors for fingerprint matching a novel minutiae based fingerprint matching algorithm is proposed a minutiae matching algorithm has to solve two problems correspondence and similarity computation for the correspondence problem we assign each minutia two descriptors texture based and minutiae based descriptors and use an alignment based greedy matching algorithm to establish the correspondences between minutiae for the similarity computation we extract a 17 d feature vector from the matching result and convert the feature vector into a matching score using support vector classifier the proposed algorithm is tested on fvc2002 databases and compared to all participators in fvc2002 according to equal error rate the proposed algorithm ranks 1st on db3 the most difficult database in fvc2002 and on the average ranks 2nd on all 4 databases

robust and efficient ridge based palmprint matching during the past decade many efforts have been made to use palmprints as a biometric modality however most of the existing palmprint recognition systems are based on encoding and matching creases which are not as reliable as ridges this affects the use of palmprints in large scale person identification applications where the biometric modality needs to be distinctive as well as insensitive to changes in age and skin conditions recently several ridge based palmprint matching algorithms have been proposed to fill the gap major contributions of these systems include reliable orientation field estimation in the presence of creases and the use of multiple features in matching while the matching algorithms adopted in these systems simply follow the matching algorithms for fingerprints however palmprints differ from fingerprints in several aspects 1 palmprints are much larger and thus contain a large number of minutiae 2 palms are more deformable than fingertips and 3 the quality and discrimination power of different regions in palmprints vary significantly as a result these matchers are unable to appropriately handle the distortion and noise despite heavy computational cost motivated by the matching strategies of human palmprint experts we developed a novel palmprint recognition system the main contributions are as follows 1 statistics of major features in palmprints are quantitatively studied 2 a segment based matching and fusion algorithm is proposed to deal with the skin distortion and the varying discrimination power of different palmprint regions and 3 to reduce the computational complexity an orientation field based registration algorithm is designed for registering the palmprints into the same coordinate system before matching and a cascade filter is built to reject the nonmated gallery palmprints in early stage the proposed matcher is tested by matching 840 query palmprints against a gallery set of 13 736 palmprints experimental results show that the proposed matcher outperforms the existing matchers a lot both in matching accuracy and speed

computation of diagnosable fault occurrence indices for systems with repeatable faults certain faults such as intermittent or non persistent faults may occur repeatedly for discrete event systems prone to repeated faults jiang kumar and garcia in 2003 introduced the notion of l diagnosability requiring the diagnosis of the l th occurrence of a fault within a bounded delay the present paper studies the identification of the set of all indices l for which the system is not l diagnosable these are precisely the occurrence indices for which a repeatable fault cannot be diagnosed we present an algorithm of cubic complexity to determine whether a system is diagnosable for every fault occurrence index for those systems for which the answer is negative we show that the set of indices for which the system is non diagnosable possesses the property that it is either finite or consists of a finite number of eventually periodic sets

efficient spectral galerkin methods iii polar and cylindrical geometries we present in this paper several extremely efficient and accurate spectral galerkin methods for second and fourth order equations in polar and cylindrical geometries these methods are based on appropriate variational formulations which incorporate naturally the pole condition s in particular the computational complexities of the chebyshev galerkin method in a disk and the chebyshev legendre galerkin method in a disk or a cylinder are quasi optimal optimal up to a logarithmic term as an indication of efficiency the cpu time for the poisson solver on a disk by our chebyshev galerkin method is only about 70 of the corresponding finite difference code in fishpack

shape matching and object recognition using shape contexts we present a novel approach to measuring similarity between shapes and exploit it for object recognition in our framework the measurement of similarity is preceded by 1 solving for correspondences between points on the two shapes 2 using the correspondences to estimate an aligning transform in order to solve the correspondence problem we attach a descriptor the shape context to each point the shape context at a reference point captures the distribution of the remaining points relative to it thus offering a globally discriminative characterization corresponding points on two similar shapes will have similar shape contexts enabling us to solve for correspondences as an optimal assignment problem given the point correspondences we estimate the transformation that best aligns the two shapes regularized thin plate splines provide a flexible class of transformation maps for this purpose the dissimilarity between the two shapes is computed as a sum of matching errors between corresponding points together with a term measuring the magnitude of the aligning transform we treat recognition in a nearest neighbor classification framework as the problem of finding the stored prototype shape that is maximally similar to that in the image results are presented for silhouettes trademarks handwritten digits and the coil data set

combining weighted linear project analysis with orientation diffusion for fingerprint orientation field reconstruction this paper presents a novel algorithm for reconstructing the fingerprint orientation field fof the basic idea of the algorithm is to reconstruct the fof by combining weighted linear project analysis with orientation diffusion we first compute the weight values of point gradients according to the similarity of point orientations in the second procedure the qualities of blocks are assessed by the coherence of point orientations and then the block orientation with high quality are estimated by the weighted linear projection analysis based on the vector set of point gradients the fingerprint blocks that will be reconstructed is selected by the priority of them in the third procedure in the end the fof is reconstructed by orientation diffusion based on the reconstruction priorities of blocks to validate the performance the proposed method has been applied to fingerprint enhancement fingerprint singularity detection fingerprint minutiae extraction and fingerprint matching using the fvc2000 and fvc2004 databases the experiments show that the proposed method is more accurate and more reliable and it is more robust against noise

stable and efficient spectral methods in unbounded domains using laguerre functions stable and efficient spectral methods using laguerre functions are proposed and analyzed for model elliptic equations on regular unbounded domains it is shown that spectral galerkin approximations based on laguerre functions are stable and convergent with spectral accuracy in the usual not weighted sobolev spaces efficient accurate and well conditioned algorithms using laguerre functions are developed and implemented numerical results indicating the spectral convergence rate and effectiveness of these algorithms are presented

orthogonal rational functions on a semi infinite interval abstract by applying a mapping to the chebyshev polynomials we define a new spectral basis the rational chebyshev functions on the semi infinite interval denoted by tl n y continuing earlier work by the author and by grosch and orszag we show that these rational functions inherit most of the good numerical characteristics of the chebyshev polynomials orthogonality completeness exponential or infinite order convergence matrix sparsity for equations with polynomial coefficients and simplicity seven numerical examples illustrate their versatility the charney stability problem of meteorology for example is solved to show the feasibility of applying spectral methods to a semi infinite atmosphere for functions that are singular at both endpoints such as k 1 y one may combine rational chebyshev functions with a preliminary mapping to obtain a single exponentially convergent expansion on y 0 finally we successfully generalize the wkb method to obtain for the j 0 bessel function an amplitude phase approximation which is convergent rather than asymptotic and is accurate not merely for large y but for all y even the origin

laguerre galerkin method for nonlinear partial differential equations on a semi infinite interval summary a laguerre galerkin method is proposed and analyzed for the burgers equation and benjamin bona mahony bbm equation on a semi infinite interval by reformulating these equations with suitable functional transforms it is shown that the laguerre galerkin approximations are convergent on a semi infinite interval with spectral accuracy an efficient and accurate algorithm based on the laguerre galerkin approximations to the transformed equations is developed and implemented numerical results indicating the high accuracy and effectiveness of this algorithm are presented

motion trajectory reproduction from generalized signature description free form motion trajectories prove to be an informative and compact motion clue in sketching long term spatiotemporal motions hence motion trajectories have been used for characterizing human behaviors activities robot actions and other objects movements however it is observed that most of the previous studies merely use motion trajectories straightforwardly in the raw data form which is inflexible as they rely largely on the absolute positions to solve this problem we propose to achieve effective motion trajectory descriptions by developing a systematic trajectory description mechanism to this end a flexible motion trajectory signature descriptor has been proposed in our previous work which can offer generalized descriptions to the raw trajectory data thanks to its rich description invariants moreover for an effective descriptor it is sometimes desired to have mutual description functions i e describing and un describing capability to support some applications like robot learning hence opposite to describing a motion trajectory using the signature this paper focuses on the un describing problem that is reproducing a trajectory instance from a given signature description the moving frame technique is used in formulating the trajectory reproduction method a nonlinear signature matching based metric is also developed to measure the quality of the reproductions experiments are conducted to verify the effectiveness of the trajectory reproduction it is shown that the trajectory signature is flexible and easy to implement in both the description and reproduction of trajectory instances

efficient spectral galerkin method ii direct solvers of second and fourth order equations using chebyshev polynomials efficient direct solvers based on the chebyshev galerkin methods for second and fourth order equations are presented they are based on appropriate base functions for the galerkin formulation that lead to discrete systems with special structured matrices that can be efficiently inverted numerical results indicate that the direct solvers presented in this paper are significantly more accurate and efficient than those based on the chebyshev tau method

efficient spectral galerkin methods iv spherical geometries fast spectral galerkin algorithms are developed for elliptic equations on the sphere the algorithms are based on a double fourier expansion and have quasi optimal optimal up to a logarithmic term computational complexity numerical experiments indicate that they are significantly more efficient and or accurate when compared with the algorithms based on spherical harmonics and on finite difference extensions to problems in spherical layers and to vector equations are also discussed

the hermite spectral method for gaussian type functions although hermite functions were widely used for many practical problems numerical experiments with the standard normalized hermite functions psi n v worked poorly in the sense that too many hermite functions are required to solve differential equations in order to obtain accurate numerical solutions it is necessary to choose a scaling factor alpha and use psi n alpha v as the basis functions in this paper the scaling factors are given for functions that are of gaussian type which have finite supports m m the scaling factor used is max 0 leqq j leqq n gamma j m where gamma j j 0 n are the roots of psi n 1 v and n 1 is the number of the truncated terms used the numerical results show that after using this scaling factor only reasonable numbers of the hermite functions are required to solve differential equations

fingerprint matching using an orientation based minutia descriptor we introduce a novel fingerprint representation scheme that relies on describing the orientation field of the fingerprint pattern with respect to each minutia detail this representation allows the derivation of a similarity function between minutiae that is used to identify corresponding features and evaluate the resemblance between two fingerprint impressions a fingerprint matching algorithm based on the proposed representation is developed and tested with a series of experiments conducted on two public domain collections of fingerprint images the results reveal that our method can achieve good performance on these data collections and that it outperforms other alternative approaches implemented for comparison

efficient spectral galerkin method i direct solvers of second and fourth order equations using legendre polynomials this paper presents some efficient algorithms based on the legendre galerkin approximations for the direct solution of the second and fourth order elliptic equations the key to the efficiency of these algorithms is to construct appropriate base functions which lead to systems with sparse matrices for the discrete variational formulations the complexities of the algorithms are a small multiple of n d 1 operations for a d dimensional domain with n 1 d unknowns while the convergence rates of the algorithms are exponential for problems with smooth solutions in addition the algorithms can be effectively parallelized since the bottlenecks of the algorithms are matrix matrix multiplications