fingerprint orientation field reconstruction by weighted discrete cosine transform orientation field represents the topological structure of the interleaved ridge and valley flows in fingerprint images although a number of methods have been proposed for orientation estimation reliable computation of orientation field is still a challenging problem due to the poor quality of some fingerprints this paper proposes a method to reconstruct fingerprint orientation field by weighted discrete cosine transform dct first the dct functions are used to build the basis atoms for linear representation of orientation field then the dct basis atoms of low and high orders are combined with the weights determined by singularity measurements for orientation reconstruction the weighted dct model is further extended for partial fingerprints to gradually and iteratively reconstruct the orientations in noisy or missing parts of fingerprints the proposed method can perform well in smoothing out the noise while maintaining the orientation details in singular regions extensive experiments have been done to compare the proposed method with some existing methods on nist and fvc fingerprint databases in terms of the reconstruction accuracy of orientation field fingerprint indexing performance and fingerprint recognition accuracy experimental results illustrate the effectiveness of the proposed method in reconstructing orientation fields especially for poor quality and partial fingerprints

existence of positive solutions for various boundary value problems in this paper we afford a concise approach to guarantee the existence of positive solutions for nonlinear second order ordinary differential equations with respect to various boundary conditions

successive iteration of positive solution for a discontinuous third order boundary value problem in this paper we obtain a successively iterative scheme of positive solution for the nonlinear third order two point boundary value problem u q u f t u 0 u 0 a u 1 b u 0 c where f is a caratheodory function f and q satisfy some additional monotone conditions the iterative scheme starts off with zero function and is therefore useful for computation purpose the main tool is monotone iterative technique on banach space moreover the iterative scheme is independent of the existence of lower and upper solutions

existence of positive solutions for non positive higher order bvps abstract we shall provide conditions on non positive function f t u 1 u n 1 so that the boundary value problem has at least one positive solution then we shall apply this result to establish several existence theorems which guarantee the multiple positive solutions

modeling orientation fields of fingerprints with rational complex functions abstract in this paper a novel model is proposed for the orientation field of fingerprints which can be expressed as the argument of a rational complex function it is suitable for all types of fingerprints experimental results show that it performs much better than the previous works

on the existence and nonexistence of positive solutions for nonlinear sturm liouville boundary value problems abstract in this paper the existence and nonexistence results of positive solutions are obtained for sturm liouville boundary value problem p x u q x u f x u x 0 1 a u 0 b p 0 u 0 0 c u 1 d p 1 u 1 0 where p c 1 0 1 q c 0 1 p x 0 q x 0 for x 0 1 f c 0 1 r a b c d 0 are constants and satisfy a b c d 0 the discussion is based on the positivity estimation for the green s function of associated linear boundary value problem and the fixed point index theory in cones

convex graph invariant relaxations for graph edit distance the edit distance between two graphs is a widely used measure of similarity that evaluates the smallest number of vertex and edge deletions insertions required to transform one graph to another it is np hard to compute in general and a large number of heuristics have been proposed for approximating this quantity with few exceptions these methods generally provide upper bounds on the edit distance between two graphs in this paper we propose a new family of computationally tractable convex relaxations for obtaining lower bounds on graph edit distance these relaxations can be tailored to the structural properties of the particular graphs via convex graph invariants specific examples that we highlight in this paper include constraints on the graph spectrum as well as tractable approximations of the stability number and the maximum cut values of graphs we prove under suitable conditions that our relaxations are tight i e exactly compute the graph edit distance when one of the graphs consists of few eigenvalues we also validate the utility of our framework on synthetic problems as well as real applications involving molecular structure comparison problems in chemistry

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

global models for the orientation field of fingerprints an approach based on quadratic differentials quadratic differentials naturally define analytic orientation fields on planar surfaces we propose to model orientation fields of fingerprints by specifying quadratic differentials models for all fingerprint classes such as arches loops and whorls are laid out these models are parametrised by few geometrically interpretable parameters which are invariant under euclidean motions we demonstrate their ability in adapting to given observed orientation fields and we compare them to existing models using the fingerprint images of the nist special database 4 we also illustrate that these model allow for extrapolation into unobserved regions this goes beyond the scope of earlier models for the orientation field as those are restricted to the observed planar fingerprint region within the framework of quadratic differentials we are able to verify analytically penrose s formula for the singularities on a palm l s penrose dermatoglyphics scientific american vol 221 no 6 pp 73 84 1969 potential applications of these models are the use of their parameters as indices of large fingerprint databases as well as the definition of intrinsic coordinates for single fingerprint images

finite element model of ionic nanowires with size dependent mechanical properties determined by ab initio calculations a finite element procedure for modeling crystalline nanostructures such as nanowires is proposed the size effects exhibited by nano objects are captured by taking into account a surface energy following the classical gurtin murdoch surface elasticity theory an appropriate variational form and a finite element approach are provided to model and solve relevant problems numerically we describe a simplified technique based on projection operators for constructing the surface elements the methodology is completed with a computational procedure based on ab initio calculations to extract elastic coefficients of general anisotropic surfaces the fem continuum model is validated by comparisons with complete ab initio models of nanowires with different diameters where size dependent mechanical properties are observed the fem continuum model can then be used to model similar nanostructures in ranges of sizes or geometries where analytical or atomistic model are limited the validated model is applied to the analysis of size effects in the bending of an aln nanowire

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

fingerprint classification by directional image partitioning in this work we introduce a new approach to automatic fingerprint classification the directional image is partitioned into homogeneous connected regions according to the fingerprint topology thus giving a synthetic representation which can be exploited as a basis for the classification a set of dynamic masks together with an optimization criterion are used to guide the partitioning the adaptation of the masks produces a numerical vector representing each fingerprint as a multidimensional point which can be conceived as a continuous classification different search strategies are discussed to efficiently retrieve fingerprints both with continuous and exclusive classification experimental results have been given for the most commonly used fingerprint databases and the new method has been compared with other approaches known in the literature as to fingerprint retrieval based on continuous classification our method gives the best performance and exhibits a very high robustness

symmetric phase only matched filtering of fourier mellin transforms for image registration and recognition presents a new method to match a 2d image to a translated rotated and scaled reference image the approach consists of two steps the calculation of a fourier mellin invariant fmi descriptor for each image to be matched and the matching of the fmi descriptors the fmi descriptor is translation invariant and represents rotation and scaling as translations in parameter space the matching of the fmi descriptors is achieved using symmetric phase only matched filtering spomf the performance of the fmi spomf algorithm is the same or similar to that of phase only matched filtering when dealing with image translations the significant advantage of the new technique is its capability to match rotated and scaled images accurately and efficiently the innovation is the application of spomf to the fmi descriptors which guarantees high discriminating power and excellent robustness in the presence of noise this paper describes the principle of the new method and its discrete implementation for either image detection problems or image registration problems practical results are presented for various applications in medical imaging remote sensing fingerprint recognition and multiobject identification

intrinsic manova for riemannian manifolds with an application to kendall s space of planar shapes we propose an intrinsic multifactorial model for data on riemannian manifolds that typically occur in the statistical analysis of shape due to the lack of a linear structure linear models cannot be defined in general to date only one way manova is available for a general multifactorial model we assume that variation not explained by the model is concentrated near elements defining the effects by determining the asymptotic distributions of respective sample covariances under parallel transport we show that they can be compared by standard manova often in applications manifolds are only implicitly given as quotients where the bottom space parallel transport can be expressed through a differential equation for kendall s space of planar shapes we provide an explicit solution we illustrate our method by an intrinsic two way manova for a set of leaf shapes while biologists can identify genotype effects by sight we can detect height effects that are otherwise not identifiable

a scaling law for properties of nano structured materials in this brief communication we identify intrinsic length scales of several physical properties at the nano scale and show that for nano structures whose characteristic sizes are much larger than these scales the properties obey a simple scaling law the underlying cause of the size dependence of these properties at the nano scale is the competition between surface and bulk energies this law provides a yardstick for checking the accuracy of experimentally measured or numerically computed properties of nano structured materials over a broad size range and can thus help replace repeated and exhaustive testing by one or a few tests

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

pixel level singular point detection from multi scale gaussian filtered orientation field singular point as a global feature plays an important role in fingerprint recognition inconsistent detection of singular points apparently gives an affect to fingerprint alignment classification and verification accuracy this paper proposes a novel approach to pixel level singular point detection from the orientation field obtained by multi scale gaussian filters initially a robust pixel level orientation field is estimated by a multi scale averaging framework then candidate singular points in pixel level are extracted from the complex angular gradient plane derived directly from the pixel level orientation field the candidate singular points are finally validated via a cascade framework comprised of nested poincare indices and local feature based classification experimental results over the fvc 2000 db2 confirm that the proposed method achieves robust and accurate orientation field estimation and consistent pixel level singular point detection the experimental results exhibit a low computational cost with better performance thus the proposed method can be employed in real time fingerprint recognition

connected components of the moduli spaces of abelian differentials with prescribed singularities consider the moduli space of pairs c where c is a smooth compact complex curve of a given genus and is a holomorphic 1 form on c with a given list of multiplicities of zeroes we describe connected components of this space this classification is important in the study of dynamics of interval exchange transformations and billiards in rational polygons and in the study of geometry of translation surfaces

systematic methods for the computation of the directional fields and singular points of fingerprints the first subject of the paper is the estimation of a high resolution directional field of fingerprints traditional methods are discussed and a method based on principal component analysis is proposed the method not only computes the direction in any pixel location but its coherence as well it is proven that this method provides exactly the same results as the averaged square gradient method that is known from literature undoubtedly the existence of a completely different equivalent solution increases the insight into the problem s nature the second subject of the paper is singular point detection a very efficient algorithm is proposed that extracts singular points from the high resolution directional field the algorithm is based on the poincare index and provides a consistent binary decision that is not based on postprocessing steps like applying a threshold on a continuous resemblance measure for singular points furthermore a method is presented to estimate the orientation of the extracted singular points the accuracy of the methods is illustrated by experiments on a live scanned fingerprint database

multiplicity results for some second order four point boundary value problems abstract in this paper by using a fixed point theorem of functional type in a cone some new results for the multiplicity of positive solutions of second order four point boundary value problems are obtained the emphasis is put on the nonlinear term involved with the first order derivative

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

positive solutions to singular system with four point coupled boundary conditions abstract existence of positive solution to a nonlinear singular system with four point coupled boundary conditions of the type x t f t x t y t t 0 1 y t g t x t y t t 0 1 x 0 0 x 1 y y 0 0 y 1 x is established the nonlinearities f g 0 1 0 0 0 are continuous and singular at t 0 t 1 while the parameters satisfy 0 1 0 1 an example is included to show the applicability of our result

fingerprint ridge distance computation methodologies abstract the average ridge distance of fingerprint images is used in many problems and applications it is used in fingerprint filter design or in identification and classification procedures this paper addresses the problem of local average ridge distance computation this computation is based on a two step procedure first the average distance is defined in each significant portion of the image and then this information is propagated onto the remaining regions to complete the computation two methods are considered in the first step geometric and spectral in the geometric approach the central points of ridges are estimated on a regular grid and straight lines passing through these points and parallel to the ridge directions are used the second method is based on the computation of harmonic coefficients leading to effective estimates of the average ridge period in order to complete the average distance map a diffusion equation is used so that maps with minimum variations are favored finally some experimental results on nist sdb4 are reported

fingerprint matching based on global comprehensive similarity this paper introduces a novel algorithm based on global comprehensive similarity with three steps to describe the euclidean space based relative features among minutiae we first build a minutia simplex that contains a pair of minutiae as well as their associated textures with its transformation variant and invariant relative features employed for the comprehensive similarity measurement and parameter estimation respectively by the second step we use the ridge based nearest neighborhood among minutiae to represent the ridge based relative features among minutiae with these ridge based relative features minutiae are grouped according to their affinity with a ridge the euclidean space based and ridge based relative features among minutiae reinforce each other in the representation of a fingerprint finally we model the relationship between transformation and the comprehensive similarity between two fingerprints in terms of histogram for initial parameter estimation through these steps our experiment shows that the method mentioned above is both effective and suitable for limited memory afis owing to its less than 1k byte template size

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

on the existence of positive solutions for semilinear elliptic equations in the annulus abstract we study the existence of positive radial solutions of u g x u 0 in annuli with dirichlet dirichlet neumann boundary conditions we prove that the problems have positive radial solutions on any annulus if is sublinear at 0 and

a nonlinear orientation model for global description of fingerprints a nonlinear orientation model for the representation of the orientation matrix of a fingerprint image is presented a general procedure to obtain the set of parameters describing this model is shown particularly a piecewise linear orientation function is analysed the model compared with a previous zero pole model shows substantial decrease in the orientation error the application of this model for efficient identity verification based on the ridge orientation is explored

successive iteration and positive solution for nonlinear second order three point boundary value problems in this paper we study the existence of positive solution for two classes of nonlinear second order three point boundary value problems using some monotone iterative schemes in both cases such schemes start off with known constant functions and therefore are useful to computation purpose

a contactless fingerprint verification method using a minutiae matching technique most of matching or verification phases of fingerprint systems use minutiae types and orientation angle to find matched minutiae pairs from the input and template fingerprints unfortunately due to some non linear distortions like excessive pressure and fingers twisting during enrollment this process can cause the minutiae features to be distorted from the original the authors are then interested in a fingerprint matching method using contactless images for fingerprint verification after features extraction they compute euclidean distances between template minutiae bifurcation and ending points and input image minutiae they compute then after bifurcation ridges orientation angles and ending point orientations in the decision stage they analyze the similarity between templates the proposed algorithm has been tested on a set of 420 fingerprint images the verification accuracy is found to be acceptable and the experimental results are promising

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

eshelby formalism for nano inhomogeneities the eshelby formalism for inclusion inhomogeneity problems is extended to the nano scale at which surface interface effects become important the interior and exterior eshelby tensors for a spherical inhomogeneous inclusion with the interface stress effect subjected to an arbitrary uniform eigenstrain embedded in an infinite alien matrix and the stress concentration tensors for a spherical inhomogeneity subjected to an arbitrary remote uniform stress field are obtained unlike their counterparts at the macro scale the eshelby and stress concentration tensors are in general not uniform inside the inhomogeneity but are position dependent they have the property of radial transverse isotropy it is also shown that the size dependence of the eshelby tensors and the stress concentration tensors follow very simple scaling laws finally the eshelby formula to calculate the strain energy in the presence of the interface effect is given

nonlinear boundary value problems in hilbert spaces abstract in this paper we examine nonlinear two point boundary value problems with sturm liouville type boundary conditions in a hilbert space our technique involves using the topological transversality theorem of a granas which relies on the notions of an essential map and a priori bounds on solutions we obtain existence results for a wide class of problems with our nonlinear term satisfying a bernstein nagumo growth condition

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

fingerprint identification using graph matching abstract a new algorithm for automated fingerprint encoding and matching is presented the algorithm is intended to be insensitive to imperfections introduced during fingerprint registration such as noise distortion and displacement a fingerprint is represented in the form of a graph whose nodes correspond to ridges in the print edges of the graph connect nodes that represent neighboring or intersecting ridges hence the graph structure captures the topological relationships within the fingerprint the algorithm has been implemented and tested using a library of real life fingerprint images

ergodicity of billiard flows and quadratic differentials on considere un systeme billard de 2 objets de masses m 1 et m 2 on montre que pour un ensemble dense de paires m 1 m 2 ce systeme est ergodique

a width independent fast thinning algorithm the skeleton of a digital figure can often be regarded as a convenient alternative to the figure itself it is useful both to diminish drastically the amount of data to be handled and to simplify the computational procedures required for description and classification purposes thinning a digital figure down to its skeleton is a time consuming process when conventional sequential computers are employed the procedure we propose allows one to speed up the thinning transformation and to get a well shaped skeleton after cleaning of the input picture has been performed the pixels of the figure are labeled according to their distance from the background and a set whose pixels are symmetrically placed with respect to distinct contour parts of the figure is found this set is then given a linear structure by applying topology preserving removal operations finally a pruning step regarding branches not relevant in the framework of the problem domain completes the process the resulting skeleton is a labeled set of pixels which is shown to possess all the required properties particularly those concerning connectedness topology and shape moreover the original figure can almost completely be recovered by means of a reverse distance transformation only a fixed and small number of sequential passes through the picture is necessary to achieve the goal the computational effort is rather modest and the use of the proposed algorithm turns out to be more advantageous the greater the width of the figure to be thinned

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

on convex relaxation of graph isomorphism graphs are a ubiquitous mathematical abstraction used in numerous problems in science and engineering of particular importance is the need to find the best structure preserving matching of graphs since graph matching gm is a computationally intractable problem numerous heuristics exist to approximate its solution an important class of gm heuristics is relaxation techniques based on replacing the original problem by a continuous convex program conditions for applicability or inapplicability of such convex relaxations are poorly understood in this study we propose easy to check spectral properties to characterize a wide family of graphs for which we prove equivalence of convex relaxation to the exact gm

a combination model for orientation field of fingerprints orientation field is a global feature of fingerprints that is very important in automatic fingerprint identification systems afis establishing an accurate and concise model for orientation fields will not only improve the performance of orientation estimation but also make it feasible to apply orientation information in the matching process in this paper a novel model for the orientation field of fingerprints is proposed we use a polynomial model to approximate the orientation field globally and a point charge model at each singular point to improve the approximation locally these two models are combined together by a weight function experimental results are provided to illustrate the fact that this combination model is more accurate and robust with respect to noise compared with the previous works the application of the model is discussed at the end

three positive solutions for second order m point boundary value problems for the second order m point boundary value problemu t f t u 0 0 0 i 1 2 m 2 0 x 1 x 2 x m 2 1 growth conditions are imposed on f which yield the existence of at least three positive solutions by using the leggett williams fixed point theorem the associated green s function for the m point boundary value problem is also given

an application of topological transversality to non positive higher order difference equations in this paper we shall provide sufficient conditions on the non positive function i u 1 u n 1 so that the boundary value problem bvp given by e d nu i m i u i du i d n 2 i 0 and bc d mu 0 0 0 m n 3 a d n 2 0 b d n 1u 0 0 c d n 2u t 1 d d n 1u t 1 0 has at least one positive solution

a randomized approach with geometric constraints to fingerprint verification abstract in this paper a fuzzy bipartite weighted graph model is proposed to solve fingerprint verification problem a fingerprint image is preprocessed first to form clusters of feature points which are called feature point clusters twenty four attributes are extracted for each feature point cluster the attributes are characterized by fuzzy values attributes of an input image to be verified are considered as the set of left nodes in a fuzzy bipartite weighted graph and the attributes of claimed template fingerprint image are considered as the set of right nodes in the graph the fingerprint verification problem is thus converted into a fuzzy bipartite weighted graph matching problem a matching algorithm is proposed for the fuzzy bipartite weighted graph model to find an optimal matching with a goodness score experimental results reveal the feasibility of the proposed approach in fingerprint verification

a variational formulation for fingerprint orientation modeling orientation pattern is an important feature for characterizing fingerprint and plays critical roles in fingerprint recognition and fingerprint classification this paper proposes a framework for modeling the fingerprint orientation field based on the variational principle where the orientation pattern can be estimated through solving the associated euler lagrange equation compared with existing methods our proposed method has the following features firstly it does not require any prior information about the structure of the acquired fingerprint such as location of singular point s secondly it explicitly provides freedom for modeling the singularity in the orientation field thirdly it has less number of parameters comparison has been made with respect to state of the arts in fingerprint orientation modeling in terms of modeling accuracy fingerprint enhancement and singular point detection advantages of the proposed method are demonstrated

geometric framework for fingerprint image classification given a digitized fingerprint image we would like to classify it into one of several types already established in the literature in this paper we consider five types for classification double loop whorl left loop right loop and arch we illustrate the use of a geometric framework for a systematic top down classification of the foregoing types from the double loop type down to the arch type in the order given above the framework employs both a geometric grouping and a global geometric shape analysis of fingerprint ridges to accomplish the required task these processes are based on the framework s underlying b spline representation and interpretation of the ridges

a fast projected fixed point algorithm for large graph matching we propose a fast algorithm for approximate matching of large graphs previous graph matching algorithms suffer from high computational complexity and therefore do not have good scalability by using a new doubly stochastic projection for matching two weighted graphs of n nodes our algorithm has time complexity only o n 3 per iteration and space complexity o n 2 we proved that our algorithm converges at a super logarithmic rate experiments on large synthetic and real graphs over 1000 nodes were conducted to evaluate the performance of various algorithms results show that due to its fast convergence our algorithm is more than an order of magnitude faster than the previous state of the art algorithms while maintaining comparable accuracy in large graph matching highlightslow time complexity o n3 iteration for two graphs of n nodes super logarithm convergence guarantee large graph matching experiments