Fuzzy Object retrieval by using histogram of fuzzy Allen relations

Abstract-Relative position of object description are widely used in event understanding and computer vision tasks especially in object recognition. Use of low level features cannot give satisfactory results when high level concepts is not easily expressible in low level contents. Mostly researchers are concentrating on spatio-temporal relationship between objects or regions of an object in images. Object retrieval which is taken into account the relative position of objects in images become important. In such a case classical Allen relations are used. Searched object can take various shapes and scale according to shooting. Fuzzy methods have the ability to compensate the imprecise informations and vagueness. In this paper fuzzy histograms of Allen relations are used for object retrieval. Fuzzy histograms of Allen relations are the quantitative representation of relative object position. For this purpose Matsakis's [9] algorithm for fuzzification of line segments is refined. This representation is affine invariant. Query is made by example and only corresponding relative relation between objects is considered. Results are analyzed by a well known Receiver Operating Characteristic curve ( ROC )method

On time dependent MHD nanofluid dynamics due to enlarging sheet with bioconvection and two thermal boundary conditions

The current study pertains to heat and mass transportation of magnetic fluid flow having dilute diffusion of nanoparticles and motile microorganisms over a permeable stretched sheet to examine the influence of thermal radiation and activation energy. Similarity functions are utilized to convert the highly mixed non-linear partial differential equations into higherorder non-linear ordinary differential equations. Five coupled equations are derived to be resolved numerically by employing a computing function Bvp4c, built-in Matlab. Two sets of thermal boundaries prescribed surface temperature (PSF) and prescribed heat flux (PHF) are considered. Basic physical quantities, temperature distribution, concentration, velocity field, and motile micro-organism profiles are observed as influenced by emerging parameters. The microorganisms distribution undergoes decreasing behavior against growing values of bio-convection Lewis number and Peclet number. These results are highly useful in the application of heat-transmitting devices and microbial fuel cells. It is seen that decreasing trend is observed in velocity profile when parameters Nr and Nc are uplifted. Also, the motility of the nanofluid decreases when the Lb parameter is raised. On the other hand, an increase in Peclet number Pe showed a rising trend in motility profile. Additionally, the implications of Brownian motion, Rayleigh number, Bioconvection Lewis number thermophoresis parameter, Peclet number, and buoyancy ratio parameter are discussed. Moreover, the obtained outcomes are validated as compared to the existing ones as limiting cases. Representative findings for microorganism concentration, skin friction coefficient, temperature gradient, local Sherwood number and density number of motile microorganisms, velocity field, temperature, the volumetric concentration of nanoparticles, are discussed in tabulated and graphical form

Decision support algorithm under SV-neutrosophic hesitant fuzzy rough information with confidence level aggregation operators

To deal with the uncertainty and ensure the sustainability of the manufacturing industry, we designed a multi criteria decision-making technique based on a list of unique operators for single-valued neutrosophic hesitant fuzzy rough (SV-NHFR) environments with a high confidence level. We show that, in contrast to the neutrosophic rough average and geometric aggregation operators, which are unable to take into account the level of experts' familiarity with examined objects for a preliminary evaluation, the neutrosophic average and geometric aggregation operators have a higher level of confidence in the fundamental idea of a more networked composition. A few of the essential qualities of new operators have also been covered. To illustrate the practical application of these operators, we have given an algorithm and a practical example. We have also created a manufacturing business model that takes sustainability into consideration and is based on the neutrosophic rough model. A symmetric comparative analysis is another tool we use to show the feasibility of our proposed enhancements

Modélisation des relations spatiales entre objets en mouvement

Spatial relations between different image regions are helpful in image understanding, interpretation and computer vision applications. Spatio-temporal analysis involves the integration of spatial relations changing over time between moving objects of a dynamic scene. Spatio-temporal relations are defined for a selected time interval using 3D geometry or extension of 2D object geometry to the time dimension with sequence occurrence of primitive events for each snapshot. Modeling dynamic spatial relations takes into account the relative object position and their directional relations; this involves the topological, directional and distance relations and their logical extension to the temporal domain. In this thesis, a method for combining topological and directional relations information is discussed where 1D temporal fuzzy Allen relations are applied in spatial domain. Initially, the method has a high computational cost. This computing cost is due to the object approximation and the fuzzification algorithm of segments. The computing time has been using polygonal object approximation. Fuzzification algorithm is replaced with fuzzy aggregation operators for segments of a longitudinal section. In this method, two dimensional topological relations are represented in a histogram. The representation method for two dimensional spatial relations has been changed. These fuzzy relations are not Jointly Exhaustive and Pairwise Disjoint (JEPD). An algorithm for defuzzification of spatial relations is proposed to realize JEPD set of spatial relations, these JEPD spatial relations are represented in a neighborhood graph. In this neighborhood graph, each node represents the topological and directional relation. This method is further extended for defining spatio-temporal relations using space and time data model, a set of spatio-temporal relations are also elaborated using the stability property in topology. In an application, a method for spatio-temporal reasoning based on this new model is developed. Spatio-temporal reasoning consists of developing the composition tables for spatial relations. Composition table for topological relations are rearranged into sub-tables. Entities in these sub-tables are related to each other and mathematical rules are defined for composition of spatial relations which elaborate the relation between entities of sub-tables. In another application, we propose a method for motion event predictions between moving objects. It is a similar process to the spatio-temporal reasoning. Dynamic objects occupy different places at different time points, these objects have multiple choices for subsequent positions and a unique history. Prediction about motion events take into account the history of a moving object and predict about the semantics of a motion event.Les relations spatiales entre les différentes régions dans une image sont utiles pour la compréhension et l'interprétation de la scène représentée. L'analyse Spatio-temporelle d'une scène implique l'intégration du temps dans des relations spatiales entre les objets en mouvement. Les relations spatio-temporelles sont définies dans un intervalle de temps utilisant la géométrie 3D ou l'extension de la géométrie 2D à la dimension temporelle. La modélisation des relations spatiales dynamiques prend en compte la position relative des objets et leurs relations directionnelles, ceci implique les relations topologiques, directionnelles et de distance. Ces relations sont étendues au domaine temporel. Dans notre travail, on décrit une méthode de combinaison d’information topologique et directionnelle où les relations d'Allen floues 1D sont appliquées au domaine spatial. La méthode proposée intègre le flou au niveau des relations. La méthode très gourmande initialement en temps de calcul en raison de l’approximation des objets ainsi qu'à l'algorithme de fuzzification des segments des sections longitudinales est améliorée en utilisant une approximation polygonale adaptée sur les objets considérés. L'algorithme du fuzzification des segments d'une section longitudinale inclut des opérateurs d'agrégation floue. Dans la méthode proposée, Les relations topologiques 2Dsont représentées par un histogramme. Les relations floues n'étant pas exhaustives, un algorithme de défuzzification des relations spatiales a été proposé pour réaliser un ensemble JEPD de relations spatiales. Cet ensemble de relations spatiales est représenté par un graphe de voisinage où chaque nœud du graphe représente la relation topologique et directionnelle. Cette méthode définit des relations spatio-temporelles en utilisant le modèle de données Espace-Temps. Un ensemble de relations spatio-temporelles est également fourni à l'aide de la stabilité topologique. Afin de valider le modèle, nous avons développé des applications fondées sur le raisonnement spatio-temporel proposé. Celui-ci a permit la création de tables de composition pour les relations spatiales topologiques structurées en sous-tables. Les entités de ces sous-tables sont liées les unes aux autres par des relations spatiales. Dans une seconde application, nous avons proposé une méthode de prédiction des évènements entre objets en mouvement fondée sur le même raisonnement spatio-temporel. Les objets en mouvement changeant de position à chaque instant, la prédiction de la nouvelle position spatiale d'un objet tient compte des états de relations spatiales calculées précédemment

Modeling spatial relations between moving objects

Les relations spatiales entre les différentes régions dans une image sont utiles pour la compréhension et l'interprétation de la scène représentée. L'analyse Spatio-temporelle d'une scène implique l'intégration du temps dans des relations spatiales entre les objets en mouvement. Les relations spatio-temporelles sont définies dans un intervalle de temps utilisant la géométrie 3D ou l'extension de la géométrie 2D à la dimension temporelle. La modélisation des relations spatiales dynamiques prend en compte la position relative des objets et leurs relations directionnelles, ceci implique les relations topologiques, directionnelles et de distance. Ces relations sont étendues au domaine temporel. Dans notre travail, on décrit une méthode de combinaison d’information topologique et directionnelle où les relations d'Allen floues 1D sont appliquées au domaine spatial. La méthode proposée intègre le flou au niveau des relations. La méthode très gourmande initialement en temps de calcul en raison de l’approximation des objets ainsi qu'à l'algorithme de fuzzification des segments des sections longitudinales est améliorée en utilisant une approximation polygonale adaptée sur les objets considérés. L'algorithme du fuzzification des segments d'une section longitudinale inclut des opérateurs d'agrégation floue. Dans la méthode proposée, Les relations topologiques 2Dsont représentées par un histogramme. Les relations floues n'étant pas exhaustives, un algorithme de défuzzification des relations spatiales a été proposé pour réaliser un ensemble JEPD de relations spatiales. Cet ensemble de relations spatiales est représenté par un graphe de voisinage où chaque nœud du graphe représente la relation topologique et directionnelle. Cette méthode définit des relations spatio-temporelles en utilisant le modèle de données Espace-Temps. Un ensemble de relations spatio-temporelles est également fourni à l'aide de la stabilité topologique. Afin de valider le modèle, nous avons développé des applications fondées sur le raisonnement spatio-temporel proposé. Celui-ci a permit la création de tables de composition pour les relations spatiales topologiques structurées en sous-tables. Les entités de ces sous-tables sont liées les unes aux autres par des relations spatiales. Dans une seconde application, nous avons proposé une méthode de prédiction des évènements entre objets en mouvement fondée sur le même raisonnement spatio-temporel. Les objets en mouvement changeant de position à chaque instant, la prédiction de la nouvelle position spatiale d'un objet tient compte des états de relations spatiales calculées précédemment.Spatial relations between different image regions are helpful in image understanding, interpretation and computer vision applications. Spatio-temporal analysis involves the integration of spatial relations changing over time between moving objects of a dynamic scene. Spatio-temporal relations are defined for a selected time interval using 3D geometry or extension of 2D object geometry to the time dimension with sequence occurrence of primitive events for each snapshot. Modeling dynamic spatial relations takes into account the relative object position and their directional relations; this involves the topological, directional and distance relations and their logical extension to the temporal domain. In this thesis, a method for combining topological and directional relations information is discussed where 1D temporal fuzzy Allen relations are applied in spatial domain. Initially, the method has a high computational cost. This computing cost is due to the object approximation and the fuzzification algorithm of segments. The computing time has been using polygonal object approximation. Fuzzification algorithm is replaced with fuzzy aggregation operators for segments of a longitudinal section. In this method, two dimensional topological relations are represented in a histogram. The representation method for two dimensional spatial relations has been changed. These fuzzy relations are not Jointly Exhaustive and Pairwise Disjoint (JEPD). An algorithm for defuzzification of spatial relations is proposed to realize JEPD set of spatial relations, these JEPD spatial relations are represented in a neighborhood graph. In this neighborhood graph, each node represents the topological and directional relation. This method is further extended for defining spatio-temporal relations using space and time data model, a set of spatio-temporal relations are also elaborated using the stability property in topology. In an application, a method for spatio-temporal reasoning based on this new model is developed. Spatio-temporal reasoning consists of developing the composition tables for spatial relations. Composition table for topological relations are rearranged into sub-tables. Entities in these sub-tables are related to each other and mathematical rules are defined for composition of spatial relations which elaborate the relation between entities of sub-tables. In another application, we propose a method for motion event predictions between moving objects. It is a similar process to the spatio-temporal reasoning. Dynamic objects occupy different places at different time points, these objects have multiple choices for subsequent positions and a unique history. Prediction about motion events take into account the history of a moving object and predict about the semantics of a motion event

Fuzzy Difference Operators for Spatial Change Detection in 2D Spatial Scene

Fuzzy difference operators are used in different fields of decision making processes, image analysis and computer vision applications. Change detection in a spatial scene is the basic issue in modeling relative motion between object pair. Many approaches are adopted to change detection in a spatial scene and change in spatial relations is one of them. Separate methodologies are adapted to determine the change in topological, directional and distance relations. In this paper, a methodology for detection of a spatial change based on fuzzy matrix calculus is presented. Difference of combined fuzzy topological and directional relations matrices is determined by fuzzy difference operators. Experiments are performed to validate the proposed method and the promising results are obtained

Two-Dimensional Fuzzy Spatial Relations: A New Way of Computing and Representation

Fuzziness is found everywhere, in modeling spatial relations, fuzziness is found at object level as well as in relation semantics. Commonly, fuzzy topological relations are computed between fuzzy objects. Fuzziness in relation semantics is represented by fuzzy topological relations between crisp objects and these types of fuzzy topological relations are much less developed. In this paper, we propose a method for combining fuzzy topological and directional relations. We also propose an algorithm for defuzzification of relations which provides us a binary topological and directional relation between a 2D object pair. These relations are represented in a neighborhood graph. For validation and assessment, a number of experiments have been performed on artificial data

Oblique stagnation point flow of magnetized Maxwell fluid over a stretchable Riga plate with Cattaneo-Christov heat flux and convective conditions

Abstract The current work deals with the oblique stagnation point flow phenomenon of a rate-type Maxwell fluid with the significance of the Cattaneo-Christov double diffusion theory. The Cattaneo-Christov theory is illustrated through the modified form of Fourier’s and Fick’s laws. The steady magnetized flow mechanism is observed in two dimensions through a stretchable convective Riga plate. In the mass and heat transfer analysis, the consequences of chemical reactions and thermal radiation are also incorporated. With the contribution of relevant dimensionless quantities, the setup of dimensionless equations is acquired which further takes the form of nonlinear equations. The physical significance of the numerous parameters on different features of the flow phenomenon is graphically exhibited. The interesting physical quantities are computed and numerically evaluated relative to the pertinent parameters. This study reveals that the thermal relaxation time parameter lowers the rate of heat transfer, and the thermal Biot number enhances the rate of heat transport. Moreover, the Deborah number minimizes the flow field of both tangential and axial velocities

Switching Point Solution of Second-Order Fuzzy Differential Equations Using Differential Transformation Method

The first-order fuzzy differential equation has two possible solutions depending on the definition of differentiability. The definition of differentiability changes as the product of the function and its first derivative changes its sign. This switching of the derivative’s definition is handled with the application of min, max operators. In this paper, a numerical technique for solving fuzzy initial value problems is extended to solving higher-order fuzzy differential equations. Fuzzy Taylor series is used to develop the fuzzy differential transformation method for solving this problem. This leads to a single solution for higher-order differential equations