Medical professionals need help finding tumours in the ground truth image of brain because tumours’ location, contrast, intensity, size, and shape vary between images different acquisition methods, modalities, patient’s age. The medical examiner has difficulty manually separating a tumour from other parts Magnetic Resonance Imaging (MRI) image. Many semi- fully automated detection systems have ...

The high spectral resolution of hyperspectral images (HSIs) provides rich information but causes data redundancy, which imposes a computational burden on practical applications. Band selection methods can select subset HSI without changing the main to reduce dimension. Clustering-based band correlation significantly, traditional clustering are mostly hard and not accurate enough partition bands...

Kindergartens have been expected to take on a new role of child-raising support due to changes in the social environment such as declining birthrate and deregulation. A web page can be an important means for parents to gather information on the kindergarten efficiently and a web page can strongly influence the parents’ satisfaction of the kindergarten. The paper first clarifies what parents hop...

Segmentation and classification of satellite imagery are a challenging problem due to the fact that it is not feasible to execute this task on a pixel-by-pixel basis.This paper proposes an efficient image classification technique for satellite images with the aid of KFCM and artificial neural network. The proposed classification technique is made of four phases namely, pre-processing, fragmenta...

This paper introduces an evaluation methodologies for the e-learners’ behaviour that will be a feedback to the decision makers in e-learning system. Learner's profile plays a crucial role in the evaluation process to improve the e-learning process performance. The work focuses on the clustering of the e-learners based on their behaviour into specific categories that represent the learner's prof...

Abstract In recent years, the researchers have perceived modifications or transformations motivated by presence of big data on definition, complexity, and future direction real world optimization problems. Big Data visualization is mainly based efficient computer system for ingesting actual producing graphical representation understanding large quantity in a fraction seconds. At same time, clus...

Image processing is an important research area in computer vision. clustering is an unsupervised study. clustering can also be used for image segmentation. there exist so many methods for image segmentation. image segmentation plays an important role in image analysis.it is one of the first and the most important tasks in image analysis and computer vision. this proposed system presents a varia...

Image segmentation plays a crucial role in many medical imaging applications. In this paper, we present a novel algorithm for fuzzy segmentation of magnetic resonance imaging (MRI) data. The algorithm is realized by modifying the objective function in the conventional fuzzy C-means (FCM) algorithm using a kernel-induced distance metric and a spatial penalty on the membership functions. Firstly,...