flow shop sequencing problem is included in np-hard problems and a number of heuristic methods have been developed to solve it. most of these methods are offered for the crisp processing time. however fuzzy algorithm is appropriate for the problems with fuzzy processing time. this paper presents a method in which an algorithm is used to minimize make span of flow shop with fuzzy processing time...

In image processing, image segmentation is one of the important tasks to extract information from the images. A variety of segmentation algorithm is developed to satisfy increasing requirement of image segmentation. Fuzzy CMeans is unsupervised method that has been applied for the variety of purposes such as clustering, classification, image segmentation and target recognition. This method can ...

In this research, first of all, the existing problems in fragmentation measurement are reviewed for the sake of its fast and reliable evaluation. Then, the available methods used for evaluation of blast results are mentioned. The produced errors especially in recognizing the rock fragments in computer-aided methods, and also, the importance of determination of their sizes in the image analysis ...

The method of evolutionary programming is used to search for the optimal solution in fuzzy clustering of images and in fuzzy boundary detection. In fuzzy evolutionary clustering, the Gibb's probability distribution is employed to model the evolution of object clusters, and the total fuzzy distance is used as a measurement of fitness. In image boundary detection, both geometrical shape and arbit...

An approach based on contourlet image fusion and reformulated fuzzy clustering for change detection in satellite images is introduced in this paper. In this approach fusion of images is used to produce difference image from log ratio and mean ratio images. An optimal difference image should retain the unchanged areas and show the changed areas. So contourlet image fusion is used to generate the...

New filter classes for multichannel image processing are introduced and analyzed. The proposed methodology constitutes a unifying and powerful framework for multichannel image processing. The new filters use fuzzy membership functions based on different distance measures among the image vectors to adapt to local data in the image. The principle behind the new nonlinear filters is explained in d...

First of all, in this paper we propose a family of fuzzy implication operators, which the generalised Luckasiewicz ́s one, and to analyse the impacts of Smets and Magrez properties on these operators. The result of this approach will be a characterisation of a proposed family of inclusion grade operators (in Bandler and Kohout ́s manner) that satisfies the axioms of Divyendu and Dogherty. Second,...

This paper concerns with the utilization of artificial intelligence borrowed techniques such as fuzzy logic for the automatic analysis of X-ray images of industrial products for defect detection. An original two stages algorithm is presented based on the feature analysis of the radiographic images obtained from the inspected product. Each object in the image is analyzed using fuzzy logic techni...

Image thresholding is a necessary task in some image processing applications. However, due to disturbing factors, e.g. non-uniform illumination, or inherent image vagueness, the result of image thresholding is not always satisfactory. In recent years, various researchers have introduced new thresholding techniques based on fuzzy set theory to overcome this problem. Regarding images as fuzzy set...