In this paper, the fuzzy coding histogram representation for an image region is proposed for visual tracking. At the initial frame, we use the fuzzy clustering technology on all pixels within the initial detection box to get the cluster prototypes, which are used to construct the fuzzy codebook. During the tracking period, the candidate image region is also represented by a fuzzy coding histogr...

In the paper, a three-level thresholding method for image segmentation is presented, based on probability partition, fuzzy partition and entropy theory. A new fuzzy entropy has been defined through probability analysis. The image is divided into three parts, namely, dark, gray and white part, whose member functions of the fuzzy region are Z-function and P-function and S-function, respectively, ...

Fuzzy C-Means (FCM) and hard clustering are the most common tools for data partitioning. However, the presence of noisy observations in the data may cause generation of completely unreliable partitions from these clustering algorithms. Also, application of the Euclidean distance in FCM only produces spherical clusters. In this paper, a new noise-rejection clustering algorithm based on Mahalanob...

In current study, a particle swarm clustering method is suggested for clustering triangular fuzzy data. This clustering method can find fuzzy cluster centers in the proposed method, where fuzzy cluster centers contain more points from the corresponding cluster, the higher clustering accuracy. Also, triangular fuzzy numbers are utilized to demonstrate uncertain data. To compare triangular fuzzy ...

We present the simple and fast symmetry plain detection algorithm, that recognizes Falx cerebri curve on each human brain computed thomogrpahy slice. Symmetry curves appear approximately on 30% images and using such images as reference it is possible to determine symmetry plane. We propose an algorithm based on hybrid methods, that allows detect symmetry plane with deviation angle until 25. The...

In this paper, a look-up table control strategy derived from a fuzzy logic controller is developed for output regulation of a SISO linear plant with delay subject to load changes and transfer between different operating points. The strategy considers an off-line trained look-up table for rejection of an unity load step change and another one trained for unity reference step tracking combined in...

This study proposes a combination of a fuzzy sliding mode controller (FSMC) with integral-proportion-Derivative switching surface based superconducting magnetic energy storage (SMES) and PID tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. The goal of design is to improve the dynamic response of power systems after load demand changes. In t...

In this paper Genetic Algorithm based Fuzzy Logic Controller for temperature control in a plastic extrusion is developed and tested through a simulation study. A novel GA based FLC method is implemented to design a practicable advanced controller. Manifest feature of the proposed method is smoothing of undesired control signal of mamdani type FLC controller. Plastic extrusion system is generall...

This paper exposes an algorithm which leads to a fuzzy segmentation. This algorithm performs, as in the watershed method, a progressive flood of the gradient image from pixels of lowest gradients. It uses a new distance, called topographic distance. Any local minimum of the gradient norm image constitutes a seed for the region growing, avoiding the use of a marker image. These seeds constitute ...

In this paper, optimization of a linear objective function with fuzzy relational inequality constraints is investigated where the feasible region is formed as the intersection of two inequality fuzzy systems and Hamacher family of t-norms is considered as fuzzy composition. Hamacher family of t-norms is a parametric family of continuous strict t-norms, whose members are decreasing functions of ...