discontinuous transition from free flow to synchronized flow induced by short range interaction between vehicles in a three phase traffic flow model abstract in this paper we incorporate a limitation on the interaction range between neighboring vehicles into the cellular automaton model proposed by gao and jiang et al k gao r jiang s x hu b h wang and q s wu phys rev e 76 2007 026105 which was established within the framework of kerner s three phase traffic theory and has been shown to be able to reproduce the three phase traffic flow this modification eliminates an unrealistic phenomenon found in the previous model where the velocity adaptation effect between neighboring vehicles can exist even if those vehicles are infinitely far away from each other therefore in the improved model we regulate that such interactions can only occur within a finite distance for simplicity we suppose a constant value to describe this distance in this paper as a result when compared to the previous model the improved model mainly simulates the following results which are believed to be an improvement 1 the improved model successfully reproduces the expected discontinuous transition from free flow to synchronized flow and the related moving synchronized flow pattern which are both absent in the original model but have been observed in real traffic 2 the improved model simulates the correlation functions time headway distributions and optimal velocity functions which are all more consistent with the empirical data than the previous model and most of the other models published before 3 together with the previous two models considering the velocity difference effect this model finally accomplishes a significative process of developing traffic flow models from the traditional fundamental diagram approach to the three phase traffic theory this process should be helpful for us to understand the traffic dynamics and mechanics further and deeper

periodicity directionality and randomness wold features for image modeling and retrieval one of the fundamental challenges in pattern recognition is choosing a set of features appropriate to a class of problems in applications such as database retrieval it is important that image features used in pattern comparison provide good measures of image perceptual similarities we present an image model with a new set of features that address the challenge of perceptual similarity the model is based on the 2d wold decomposition of homogeneous random fields the three resulting mutually orthogonal subfields have perceptual properties which can be described as periodicity directionality and randomness approximating what are indicated to be the three most important dimensions of human texture perception the method presented improves upon earlier wold based models in its tolerance to a variety of local inhomogeneities which arise in natural textures and its invariance under image transformation such as rotation an image retrieval algorithm based on the new texture model is presented different types of image features are aggregated for similarity comparison by using a bayesian probabilistic approach the effectiveness of the wold model at retrieving perceptually similar natural textures is demonstrated in comparison to that of two other well known pattern recognition methods the wold model appears to offer a perceptually more satisfying measure of pattern similarity while exceeding the performance of these other methods by traditional pattern recognition criteria examples of natural scene wold texture modeling are also presented

understanding interarrival and interdeparture time statistics from interactions in queuing systems abstract we discuss the statistics of long queues in which the interdeparture time statistics is dominated by spatial interactions among the elements in a queue rather than the arrival or exit processes based on a fokker planck approach it is possible to calculate the stationary distance distribution among the elements in a queue as a function of their interaction potential the results relate to the ones known from random matrix theory together with the velocity distribution one can determine the time gap distribution as well this yields an analytical approach to the interdeparture and interarrival time distributions of queuing systems with spatially interacting elements while these distributions are usually determined from empirical data or from theoretical assumptions about the arrival or exit process we offer here an alternative interpretation of interdeparture time distributions as an effect of interactions in a queue this is relevant for the understanding of traffic and production systems and for the optimization of the statistical behavior of some queuing systems

spacetime texture representation and recognition based on a spatiotemporal orientation analysis this paper is concerned with the representation and recognition of the observed dynamics i e excluding purely spatial appearance cues of spacetime texture based on a spatiotemporal orientation analysis the term spacetime texture is taken to refer to patterns in visual spacetime x y t that primarily are characterized by the aggregate dynamic properties of elements or local measurements accumulated over a region of spatiotemporal support rather than in terms of the dynamics of individual constituents examples include image sequences of natural processes that exhibit stochastic dynamics e g fire water and windblown vegetation as well as images of simpler dynamics when analyzed in terms of aggregate region properties e g uniform motion of elements in imagery such as pedestrians and vehicular traffic spacetime texture representation and recognition is important as it provides an early means of capturing the structure of an ensuing image stream in a meaningful fashion toward such ends a novel approach to spacetime texture representation and an associated recognition method are described based on distributions histograms of spacetime orientation structure empirical evaluation on both standard and original image data sets shows the promise of the approach including significant improvement over alternative state of the art approaches in recognizing the same pattern from different viewpoints

stabilization effect of multiple drivers desired velocities in car following theory abstract in order to reveal the influence of driver s individual behavior on traffic flow more accurately a new car following model is proposed with consideration of multiple drives desired velocities the stability criterion of the new model is derived through linear stability theory and the results show that the current driver s desired velocity can stabilize traffic flow but the preceding driver s desired velocity can damage traffic stability through nonlinear analysis the traffic jamming transition characteristics near the critical point can be described by the kink antikink soliton of the mkdv equation numerical simulation confirms the analytical results which shows that the multiple drivers desired velocities play an important role in traffic evolution

a novel lattice hydrodynamic model accounting for driver s memory effect and the difference of optimal velocity on curved road abstract a novel lattice hydrodynamic model is put forward which takes the effects of driver s memory and difference of optimal velocity into account on curved road linear stability analysis for the novel model is discussed and the stability condition is deduced through nonlinear analysis the mkdv equation is deduced to explore the evolution of jams near the vertex the exact solution of the mkdv equation is also derived the influence of the above two factors on traffic stability are investigated by numerical examples both numerical and analytical results demonstrate that memory effect and the difference of optimal velocity on curved road can ease traffic jams efficiently

numerical approximation of entropy solutions for hyperbolic integro differential equations scalar hyperbolic integro differential equations arise as models for e g radiating or self gravitating fluid flow we present finite volume schemes on unstructured grids applied to the cauchy problem for such equations for a rather general class of integral operators we show convergence of the approximate solutions to a possibly discontinuous entropy solution of the problem for a specific model problem in radiative hydrodynamics we introduce a convergent fully discrete finite volume scheme under the assumption of sufficiently fast spatial decay of the entropy solution we can even establish the convergence rate h1 4 ln h where h denotes the grid parameter the convergence proofs rely on appropriate variants of the classical kruzhkov method for local balance laws together with a truncation technique to cope with the nonlocal character of the integral operator

new equilibrium function of traffic flow abstract using nonlinear stability theory in macroscopic traffic flow model we proposed a new equilibrium function starting from the existing equilibrium functions the kinematic wave velocity at jam density yielded by this equilibrium function is consistent with the empirical value and this equilibrium function is related to the critical stability in higher density interval

derivation properties and simulation of a gas kinetic based nonlocal traffic model we derive macroscopic traffic equations from specific gas kinetic equations dropping some of the assumptions and approximations made in previous papers the resulting partial differential equations for the vehicle density and average velocity contain a non local interaction term which is very favorable for a fast and robust numerical integration so that several thousand freeway kilometers can be simulated in real time the model parameters can be easily calibrated by means of empirical data they are directly related to the quantities characterizing individual driver vehicle behavior and their optimal values have the expected order of magnitude therefore they allow to investigate the influences of varying street and weather conditions or freeway control measures simulation results for realistic model parameters are in good agreement with the diverse non linear dynamical phenomena observed in freeway traffic

validated solutions of initial value problems for ordinary differential equations compared to standard numerical methods for initial value problems ivps for ordinary differential equations odes validated methods for ivps for odes have two important advantages if they return a solution to a problem then 1 the problem is guaranteed to have a unique solution and 2 an enclosure of the true solution is produced the authors survey taylor series methods for validated solutions of ivps for odes describe several such methods in a common framework and identify areas for future research

self stabilizing analysis of an extended car following model with consideration of expected effect abstract in this paper an extended car following model considers expected effects and self stabilizing control the self stabilizing control is applied to the new model by employing the anticipation velocity and the anticipation optimal velocity of the considered vehicle the theoretical analysis and numerical simulation are combined to carry out this paper the stability conditions can be derived from linear stability analysis moreover by using nonlinear analysis method the time dependent ginzburg landau tdgl equation and the modified kdv equation near critical point is derived by the reductive perturbation method finally theoretical results are in agreement with numerical simulation results confirming the correctness of the theoretical analysis results we demonstrate that self stabilizing control plays a positive part in restraining traffic congestion the results reveal that the expected time between the current velocity and the expected velocity has an important impact on the stability of traffic flow

new control strategy for the lattice hydrodynamic model of traffic flow abstract the new delayed feedback control strategy is applied for lattice hydrodynamic model of traffic flow by considering the control signal of the variation rate of the optimal velocity the linear stability condition is derived in the frequency domain with control theory then different feedback gains under the periodic boundary scenery and on ramp scenery are simulated the periodic boundary scenery provides an initial small disturbance situation on the circle road while the on ramp scenery reproduces the disturbance triggered by the on ramp on the open road both the theoretical analysis and simulations show that this new control signal has a positive effect to suppress traffic jams

kuramoto sivashinsky dynamics on the center unstable manifold this paper studies the dynamical behavior of solutions of the kuramoto sivashinsky partial differential equation with periodic boundary conditions on a spatial interval 0 h the length h is the bifurcation parameter and reduction is made to a two complex dimensional system on a local center unstable manifold near the second bifurcation point h 2 from the trivial solution the resulting o 2 equivariant system displays all the behavior found in high precision simulations of the partial differential equation near this bifurcation point in particular bifurcation sequences to stable traveling waves unstable modulated traveling waves and attracting heteroclinic cycles are reproduced qualitatively and quantitatively within 1 in the parameter range h 2 pm 20 a clear understanding of the global dynamical behavior in this region is thus obtained

kdv burgers equation in a new continuum model based on full velocity difference model considering anticipation effect abstract in this paper a new continuum model based on full velocity difference car following model is developed with the consideration of driver s anticipation effect by applying the linear stability theory the new model s linear stability is obtained through nonlinear analysis the kdv burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line numerical simulation shows that the new model possesses the local cluster and it is capable of explaining some particular traffic phenomena numerical results show that when considering the effects of anticipation the traffic jams can be suppressed efficiently the key improvement of this new model is that the anticipation effect can improve the stability of traffic flow

macroscopic traffic flow modeling with adaptive cruise control the incorporation of two macroscopic approaches reflecting adaptive cruise control acc and cooperative adaptive cruise control cacc traffic dynamics in a gas kinetic gkt traffic flow model is presented the first approach was recently analyzed in the literature aiming to describe the effects induced by the acc and cacc systems due to changes of the speed of the leading car s by the introduction of an acceleration deceleration term the second approach is a novel one and is based on the introduction of a relaxation term that satisfies the time space gap principle of acc or cacc systems in both approaches the relaxation time is assigned on multiple leading vehicles in the cacc case whereas in the acc case this relaxation time is only assigned to the direct leading vehicle we numerically approximate the resulting models by an accurate and robust high resolution finite volume relaxation scheme where the nonlinear system of partial differential equations is first recast to a diagonalizable semi linear system and is then discretized by a higher order weno scheme numerical simulations investigate the effect of the different acc and cacc approaches to traffic flow macroscopic stability with respect to perturbations introduced in a ring road and to flow characteristics in open freeways with merging flows at an on ramp following from the numerical results it can be concluded that cacc vehicles increase the stabilization of traffic flow with respect to both small and large perturbations compared to acc ones further the proposed cacc approach can better improve the dynamic equilibrium capacity and traffic dynamics especially at the on ramp bottleneck a novel macroscopic modeling approach for adaptive cruise control acc in traffic flow dynamics the proposed model is incorporated to a gas kinetic gkt traffic flow model a comparison with an alternative approach from the literature is performed a high resolution relaxation finite volume discretization in space and time is implemented

using spin images for efficient object recognition in cluttered 3d scenes we present a 3d shape based object recognition system for simultaneous recognition of multiple objects in scenes containing clutter and occlusion recognition is based on matching surfaces by matching points using the spin image representation the spin image is a data level shape descriptor that is used to match surfaces represented as surface meshes we present a compression scheme for spin images that results in efficient multiple object recognition which we verify with results showing the simultaneous recognition of multiple objects from a library of 20 models furthermore we demonstrate the robust performance of recognition in the presence of clutter and occlusion through analysis of recognition trials on 100 scenes

texture roughness analysis and synthesis via extended self similar ess model the 2d fractional brownian motion fbm model provides a useful tool to model textured surfaces whose roughness is scale invariant to represent textures whose roughness is scale dependent we generalize the fbm model to the extended self similar ess model in this research we present an estimation algorithm to extract the model parameters from real texture data furthermore a new incremental fourier synthesis algorithm is proposed to generate the 2d realizations of the ess model finally the estimation and rendering methods are combined to synthesize real textured surfaces

fixed points of a destabilized kuramoto sivashinsky equation we consider the family of destabilized kuramoto sivashinsky equations in one spatial dimension u t u x x x x u x x u u x u for 0 and r for certain parameter values shock like stationary solutions have been numerically observed in this work we verify the existence of several such solutions using the framework of self consistent bounds and validated numerics

an extended car following model considering the self stabilizing driving behavior of headway abstract considering the self stabilizing driving behavior of headway an extended car following model called the self stabilizing optimal velocity ssov model is presented in this paper to show the effect of the self stabilizing driving behavior of headway the ssov model is investigated by the analytical and numerical methods by using the linear analysis method the stability condition of the ssov model is obtained and then by using the nonlinear analysis method the burgers kdv and modified kdv equations are respectively derived to describe the propagating behavior of traffic density wave in the stable unstable regions and near the critical point the numerical simulations are presented to show the valid of the analytical results and the effect of the self stabilizing driving behavior the analytical and numerical results all show that the self stabilizing driving behavior plays an important role on the stability and flux of the traffic flow

texture classification by wavelet packet signatures this correspondence introduces a new approach to characterize textures at multiple scales the performance of wavelet packet spaces are measured in terms of sensitivity and selectivity for the classification of twenty five natural textures both energy and entropy metrics were computed for each wavelet packet and incorporated into distinct scale space representations where each wavelet packet channel reflected a specific scale and orientation sensitivity wavelet packet representations for twenty five natural textures were classified without error by a simple two layer network classifier an analyzing function of large regularity d sub 20 was shown to be slightly more efficient in representation and discrimination than a similar function with fewer vanishing moments d sub 6 in addition energy representations computed from the standard wavelet decomposition alone 17 features provided classification without error for the twenty five textures included in our study the reliability exhibited by texture signatures based on wavelet packets analysis suggest that the multiresolution properties of such transforms are beneficial for accomplishing segmentation classification and subtle discrimination of texture

a parametric texture model based on joint statistics of complex wavelet coefficients we present a universal statistical model for texture images in the context of an overcomplete complex wavelet transform the model is parameterized by a set of statistics computed on pairs of coefficients corresponding to basis functions at adjacent spatial locations orientations and scales we develop an efficient algorithm for synthesizing random images subject to these constraints by iteratively projecting onto the set of images satisfying each constraint and we use this to test the perceptual validity of the model in particular we demonstrate the necessity of subgroups of the parameter set by showing examples of texture synthesis that fail when those parameters are removed from the set we also demonstrate the power of our model by successfully synthesizing examples drawn from a diverse collection of artificial and natural textures

wavelet domain multifractal analysis for static and dynamic texture classification in this paper we propose a new texture descriptor for both static and dynamic textures the new descriptor is built on the wavelet based spatial frequency analysis of two complementary wavelet pyramids standard multiscale and wavelet leader these wavelet pyramids essentially capture the local texture responses in multiple high pass channels in a multiscale and multiorientation fashion in which there exists a strong power law relationship for natural images such a power law relationship is characterized by the so called multifractal analysis in addition two more techniques scale normalization and multiorientation image averaging are introduced to further improve the robustness of the proposed descriptor combining these techniques the proposed descriptor enjoys both high discriminative power and robustness against many environmental changes we apply the descriptor for classifying both static and dynamic textures our method has demonstrated excellent performance in comparison with the state of the art approaches in several public benchmark datasets

nonlinear analysis in the aw rascle anticipation model of traffic flow in this paper the aw rascle anticipation ara model is discussed from the perspective of the capability to reproduce nonlinear traffic flow behaviors observed in real traffic for this purpose a nonlinear traffic flow stability criterion is derived by using a wavefront expansion technique the result of the nonlinear stability analysis can be used not only to judge the stability evolution of an initial traffic state but also to determine the pressure term in the ara model the kdv equation is derived from the ara model added by the viscous term with the use of the reduction perturbation method the soliton solution can be analytically obtained from the perturbed kdv equation only near the neutral stability line weighted essentially nonoscillatory schemes are employed to simulate the kdv soliton the numerical results confirm the analytical kdv soliton solution

the effect of headway variation tendency on traffic flow modeling and stabilization abstract advanced communications technology enables us to obtain the headway variation tendency hvt of the next moment in a car following scenario to maximize the benefits of the new technology we developed a new traffic flow model that takes into consideration the effect of hvt first linear analysis method is used to derive the linear stability condition that determines whether the hvt can improve traffic system stability then using the reductive perturbation method a modified kdv mkdv equation is obtained and the kink antikink solutions are derived the phase diagram of driver sensitivity against equilibrium headway is also plotted by using the neutral stability line derived from linear analysis and the coexisting line derived from nonlinear analysis this diagram demonstrates that hvt does have the ability to improve the stability of traffic stream finally the effect of hvt is validated through numerical simulations where it is evident that the information of hvt can smooth the traffic stream and prevent the formation of traffic congestion

traffic behavior in a mixture of different vehicles the car following models are extended to take into account the characteristics of different vehicles the characteristic of each car can be included in the parameter of the dimensionless delay time the traffic behavior is investigated analytically and numerically under the periodic boundary condition at a low density all the vehicles move at a constant velocity when the density is larger than the critical value the traffic flow becomes unstable and the density waves appear the jamming transition does not depend only on the mean value of the dimensionless delay time but also on the variation with increase in the variation of dimensionless delay time the jamming transition occurs at a higher value of the mean value it is found that the variation of vehicles stabilizes the traffic flow and suppresses the traffic jams the transition line obtained by the linear stability analysis is compared with the simulation result

viewpoint invariant texture description using fractal analysis image texture provides a rich visual description of the surfaces in the scene many texture signatures based on various statistical descriptions and various local measurements have been developed existing signatures in general are not invariant to 3d geometric transformations which is a serious limitation for many applications in this paper we introduce a new texture signature called the multifractal spectrum mfs the mfs is invariant under the bi lipschitz map which includes view point changes and non rigid deformations of the texture surface as well as local affine illumination changes it provides an efficient framework combining global spatial invariance and local robust measurements intuitively the mfs could be viewed as a better histogram with greater robustness to various environmental changes and the advantage of capturing some geometrical distribution information encoded in the texture experiments demonstrate that the mfs codes the essential structure of textures with very low dimension and thus represents an useful tool for texture classification

computing local surface orientation and shape from texture forcurved surfaces shape from texture is best analyzed in two stages analogous to stereopsis and structure from motion a computing the texture distortion from the image and b interpreting the texture distortion to infer the orientation and shape of the surface in the scene we model the texture distortion for a given point and direction on the image plane as an affine transformation and derive the relationship between the parameters of this transformation and the shape parameters we have developed a technique for estimating affine transforms between nearby image patches which is based on solving a system of linear constraints derived from a differential analysis one need not explicitly identify texels or make restrictive assumptions about the nature of the texture such as isotropy we use non linear minimization of a least squares error criterion to recover the surface orientation slant and tilt and shape principal curvatures and directions based on the estimated affine transforms in a number of different directions a simple linear algorithm based on singular value decomposition of the linear parts of the affine transforms provides the initial guess for the minimization procedure experimental results on both planar and curved surfaces under perspective projection demonstrate good estimates for both orientation and shape a sensitivity analysis yields predictions for both computer vision algorithms and human perception of shape from texture

the kuramoto sivashinsky equation a bridge between pde s and dynamical systems abstract through extensive numerical simulation we have characterized the transition to chaos of the solutions to the kuramoto sivashinsky equation the attracting solution manifolds undergo a complex bifurcation sequence including multimodal fixed points invariant tori traveling wave trains and homoclinic orbits we relate this behavior to earlier work where the kuramoto sivashinsky equation was shown to behave as a finite dimensional dynamical system of ordinary differential equations

multiple resolution texture analysis and classification textures are classified based on the change in their properties with changing resolution the area of the gray level surface is measured at serveral resolutions this area decreases at coarser resolutions since fine details that contribute to the area disappear fractal properties of the picture are computed from the rate of this decrease in area and are used for texture comparison and classification the relation of a texture picture to its negative and directional properties are also discussed

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

classifying dynamic textures via spatiotemporal fractal analysis the large scale images and videos are one kind of the main source of big data dynamic texture dt is essential for understanding the video sequences with spatio temporal similarities this paper presents a powerful tool called dynamic fractal analysis to dt description and classification which integrates rich description of dt with strong robustness to environmental changes the proposed dynamic fractal spectrum dfs for dt sequences is composed of two components the first one is a volumetric dynamic fractal spectrum component v dfs that captures the stochastic self similarities of dt sequences by treating them as 3d volumes the second one is a multi slice dynamic fractal spectrum component s dfs that encodes fractal structures of repetitive dt patterns on 2d slices along different views of the 3d volume to fully exploit various types of dynamic patterns in dt five measurements of dt pixels are collected for the analysis on dt sequences from different perspectives we evaluated our method on four publicly available benchmark datasets all the experimental results have demonstrated the excellent performance of our method in comparison with state of the art approaches highlightsthe dynamic multi fractal analysis is developed for dt description our method is very discriminative and robust to environmental changes a computational acceleration scheme is provided for the proposed descriptor our method exhibits excellent performance on four benchmark datasets

self sustained nonlinear waves in traffic flow in analogy to gas dynamical detonation waves which consist of a shock with an attached exothermic reaction zone we consider herein nonlinear traveling wave solutions to the hyperbolic inviscid continuum traffic equations generic existence criteria are examined in the context of the lax entropy conditions our analysis naturally precludes traveling wave solutions for which the shocks travel downstream more rapidly than individual vehicles consistent with recent experimental observations from a periodic roadway y sugiyama n j phys 10 033001 2008 our numerical calculations show that nonlinear traveling waves are attracting solutions with the time evolution of the system converging toward a wave dominated configuration theoretical principles are elucidated by considering examples of traffic flow on open and closed roadways

kdv burgers equation in the modified continuum model considering anticipation effect abstract the new continuum model mentioned in this paper is developed based on optimal velocity car following model which takes the drivers anticipation effect into account the critical condition for traffic flow is derived and nonlinear analysis shows density waves occur in traffic flow because of the small disturbance near the neutral stability line the kdv burgers equation is derived and one of the solutions is given numerical simulation is carried out to show the local cluster described by the model

stability of the car following model on two lanes in the case of two lane traffic vehicle drivers always worry about the lane changing actions from neighbor lane this paper studies the stability of a car following model on two lanes which incorporates the lateral effects in traffic the stability condition of the model is obtained by using the linear stability theory the modified korteweg de vries equation is constructed and solved and three types of traffic flows in the headway sensitivity space stable metastable and unstable are classified both analytical and simulation results show that the anxiousness about lane changing from neighbor lane indeed has influence upon people s driving behavior and the consideration of lateral effects could stabilize the traffic flows on both lanes

an extended car following model considering driver s desire for smooth driving on the curved road abstract in real traffic many driver s desire to lower the fuel consumption by driving smoothly in this paper an extended car following model considering the driver s desire for smooth driving on a curved road is proposed the desire for smooth driving can be considered as a control signal including the velocity difference between the steady and history velocity the stability conditions are obtained by the control theory and the modified korteweg de vries mkdv equation is derived via the non linear analysis method the numerical simulations are carried out to analyze the control signal the friction coefficient and radius of curved road effects on traffic flow the results show that the control signal has a positive effect on improving traffic flow stability while the stability decreases with the increase of the two other parameters

texture segmentation using fractal dimension this paper deals with the problem of recognizing and segmenting textures in images for this purpose the authors employ a technique based on the fractal dimension fd and the multi fractal concept six fd features are based on the original image the above average high gray level image the below average low gray level image the horizontally smoothed image the vertically smoothed image and the multi fractal dimension of order two a modified box counting approach is proposed to estimate the fd in combination with feature smoothing in order to reduce spurious regions to segment a scene into the desired number of classes an unsupervised k means like clustering approach is used mosaics of various natural textures from the brodatz album as well as microphotographs of thin sections of natural rocks are considered and the segmentation results to show the efficiency of the technique supervised techniques such as minimum distance and k nearest neighbor classification are also considered the results are compared with other techniques

filters random fields and maximum entropy frame towards a unified theory for texture modeling this article presents a statistical theory for texture modeling this theory combines filtering theory and markov random field modeling through the maximum entropy principle and interprets and clarifies many previous concepts and methods for texture analysis and synthesis from a unified point of view our theory characterizes the ensemble of images i with the same texture appearance by a probability distribution f i on a random field and the objective of texture modeling is to make inference about f i given a set of observed texture examples in our theory texture modeling consists of two steps 1 a set of filters is selected from a general filter bank to capture features of the texture these filters are applied to observed texture images and the histograms of the filtered images are extracted these histograms are estimates of the marginal distributions of f i this step is called feature extraction 2 the maximum entropy principle is employed to derive a distribution p i which is restricted to have the same marginal distributions as those in 1 this p i is considered as an estimate of f i this step is called feature fusion a stepwise algorithm is proposed to choose filters from a general filter bank the resulting model called frame filters random fields and maximum entropy is a markov random field mrf model but with a much enriched vocabulary and hence much stronger descriptive ability than the previous mrf models used for texture modeling gibbs sampler is adopted to synthesize texture images by drawing typical samples from p i thus the model is verified by seeing whether the synthesized texture images have similar visual appearances to the texture images being modeled experiments on a variety of 1d and 2d textures are described to illustrate our theory and to show the performance of our algorithms these experiments demonstrate that many textures which are previously considered as from different categories can be modeled and synthesized in a common framework

classifying surface texture while simultaneously estimating illumination direction we propose a novel classifier that both classifies surface texture and simultaneously estimates the unknown illumination conditions a new formal model of the dependency of texture features on lighting direction is developed which shows that their mean vectors are trigonometric functions of the illuminations tilt and slant angles this is used to develop a probabilistic description of feature behaviour which forms the basis of the new classifier given a feature set from an image of an unknown texture captured under unknown illumination conditions the algorithm first estimates the most likely illumination direction for each possible texture class these estimates are used to calculate the class likelihoods and the classification is made accordingly the ability of the classifier to estimate illuminant direction and to assign the correct class was tested on 55 real texture samples in two stages the classifier was able to accurately estimate both the tilt and the slant angles of the light source for the majority of textures and gave a 98 classification rate

characteristics of traffic flow at a non signalized intersection in the framework of game theory abstract at a non signalized intersection some vehicles violate the traffic rules to pass the intersection as soon as possible these behaviors may cause many traffic conflicts even traffic accidents in this paper a simulation model is proposed to research the effects of these behaviors at a non signalized intersection vehicle s movement is simulated by the cellular automaton ca model the game theory is introduced for simulating the intersection dynamics two types of driver participate the game process cooperator c and defector d the cooperator obey the traffic rules but the defector does not a transition process may occur when the cooperator is waiting before the intersection the critical value of waiting time follows the weibull distribution one transition regime is found in the phase diagram the simulation results illustrate the applicability of the proposed model and reveal a number of interesting insights into the intersection management including that the existence of defectors is benefit for the capacity of intersection but also reduce the safety of intersection

a theory for multiresolution signal decomposition the wavelet representation multiresolution representations are effective for analyzing the information content of images the properties of the operator which approximates a signal at a given resolution were studied it is shown that the difference of information between the approximation of a signal at the resolutions 2 sup j 1 and 2 sup j where j is an integer can be extracted by decomposing this signal on a wavelet orthonormal basis of l sup 2 r sup n the vector space of measurable square integrable n dimensional functions in l sup 2 r a wavelet orthonormal basis is a family of functions which is built by dilating and translating a unique function psi x this decomposition defines an orthogonal multiresolution representation called a wavelet representation it is computed with a pyramidal algorithm based on convolutions with quadrature mirror filters wavelet representation lies between the spatial and fourier domains for images the wavelet representation differentiates several spatial orientations the application of this representation to data compression in image coding texture discrimination and fractal analysis is discussed