The most common degradations in images is their poor contrast quality. Edge Enhancement is the art of examining images for identifying objects and judging their significance. The proposed paper uses the concept of hybrid edge detection method based on fuzzy sets and cellular learning automata to detect the gray level changes of neighbors of every pixel, and to detect the edge by using the chang...

The performance of a fuzzy k-NN rule depends on the number k and a fuzzy membership-array W[I, mR], where l and m R denote the number of classes and the number of elements in the reference set X R respectively. The proposed learning procedure consists in iterative finding such k and W which minimize the error rate estimated by the 'leaving one out' method.

w w w . i j c s t . c o m Abstract Image enhancement in Spatial Domain is the process of improving the quality of a digitally stored image by manipulating the image pixel values with the help of software. Manipulation of pixel values includes point operations, where each pixel is modified according to a particular equation that is not dependent on other pixel values so that result is more suita...

Keywords-Fuzzy reasoning, Fuzzy system, Variable weighted synthesis inference method, CRI method, Fuzzy control. 1. I N T R O D U C T I O N It is well known that fuzzy inference is a theoretical foundation of fuzzy control systems and fuzzy expert systems. At present, general fuzzy inference methods include the CRI (compositional rules of inference) method, (+,-)-centroid method, simple inferen...

One of the goals of a variety of approximate reasoning models is to cope with inference patterns more flexible than those of classical reasoning. Among them, similarity-based reasoning aims at modeling notions of resemblance or proximity among propositions and consequence relations which make sense in such a setting. One way of proceeding is to. equip the set of interpretations or possible worl...

In this paper I investigate the System of fuzzy relation equations with inf → composition. I compare this system with the system of fuzzy relation equations with sup − ∗-composition. The purpose of this contribution is to show that there are many things which are common for both systems with sup−∗ and inf →-composition operations. K e y w o r d s: System of fuzzy relation equations; sup − ∗-com...

Fuzzy extractors (Dodis et al., Eurocrypt 2004) convert repeated noisy readings of a high-entropy secret into the same uniformly distributed key. A minimum condition for the security of the key is the hardness of guessing a value that is similar to the secret, because the fuzzy extractor converts such a guess to the key. We define fuzzy min-entropy to quantify this property of a noisy source of...

I n this paper, we review a new definition of fuzzy functional dependency based on conditional probability and i ts application to approximate data reduction related to operation of projection in classical relational database in order to construct fuzzy integrity constraints [l]. W e introduce the concept of partial fuzzy functional dependency which expresses the fact that a given attribute X d...

Fuzzy-logic-based modelling and control is very efficient in dealing with imprecision and nonlinearity [1]. However, the conventional approaches for designing Fuzzy Inference Systems (FISs) are subjective, which require significant human’s efforts. Other than time consuming, the subjective approaches may not be successful if the system is too complex or uncertain. Therefore, many researchers ha...

A method for air combat sensor resource management based on fuzzy Bayesian networks (FBN) is presented. Using the fuzzy value of target information gain, target threat level and pilot command, probabilistic reasoning among the networks is carried out. Simulation results indicate that FBN method performances better in the allocation of sensor resource compared to information gain (IG) method. St...