Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some kinds...

Instruments for microanalysis are now able to provide several images of the same specimen area. In this paper, two groups of methods are described for handling these multivariate maps. One group concerns dimensionality reduction, i.e., the projection of N-dimensional data sets onto a M-dimensional parameter space (M<N). It is shown that, in addition to linear mapping which can be performed by M...

This paper presents a variation of fuzzy c-means (FCM) algorithm that provides data clustering. The proposed algorithm incorporates the local spatial information in a novel fuzzy way. The new algorithm is called Weighted Fuzzy Local Information C-Means (WFLICM). WFLICM can overcome the disadvantages of the known fuzzy Cmeans algorithm and at the same time enhances the clustering performance. Th...

Image segmentation is one of the vital steps in Image processing. It is a challenging task in segmenting MRI(Magnetic Resonance Imaging) images because these images have no linear features. But MRI images provide high quality when compared to any other imaging techniques, so it is best suited for clinical diagnosis, biomedical research, etc. This paper presents a novel approach for segmenting M...

Quay crane allocation is one of the most important scheduling plans in the container terminal. A large of production data is stored in the database of the terminal. This paper utilizes the method of data mining to analyze the problem of quay crane allocation by using these data. From the mining, valuable information has been gotten from the database. The paper chooses the fuzzy cmeans cluster a...

Image segmentation and evaluation are awfully not easy but significant tribulations in computer vision. In this article we have presented an improved FCM Watershed Algorithm for image segmentation. In this techniques, Decision based median filter used for noise removal, is best for salt and pepper noise reduction. Secondly, Fuzzy CMeans used for cluster selection and for final segmentation modi...

The inverted pendulum is a highly nonlinear and open loop unstable system. To develop an accurate model of the inverted pendulum, different linear and nonlinear methods of identification will be used. However one of the problems encountered during modeling is the collection of experimental data from the inverted pendulum system. Since the output data from the unstable system does not show enoug...

This paper proposes a construction of a new distance in the HSL color space by a combination of the distances of HSL scalar components and by using the fuzzy cmeans framework to derive a fuzzy color clustering method. The main contribution consists in introducing two particular parameters to control the balance between the hue distance and the luminosity distance in the color Euclidean distance...

Image segmentation in the medical domain is a challenging field owing to poor resolution and limited contrast. The predominantly used conventional segmentation techniques and the thresholding methods suffer from limitations because of heavy dependence on user interactions. Uncertainties prevalent in an image cannot be captured by these techniques. The performance further deteriorates when the i...

This paper proposes a pattern recognition model to develop clusters of homogenous activities for blue-collar workers in the State Qatar. The activity-based data from travel diary 1051 collected by Ministry Transportation and Communication (MoTC) Qatar was used analysis. A is applied revealed preference (RP) survey obtained workers. Raw preprocessing outliers detection filtering algorithms were ...