Image classification is the important part of remote sensing, image analysis and pattern recognition. Digital Image Classification is the process of sorting all the pixels in an image into a finite number of individual classes. Landuse/Landcover classification of satellite images is an important activity for extracting geospatial information for military & civil purposes like inaccessible areas...

An Improved Adaptive Fuzzy C-Means (IAFCM) algorithm was developed and applied to the segmentation and classification of Multicolor Fluorescence in Situ Hybridization (M-FISH) images, which can be used to detect chromosomal abnormalities for cancer and genetic disease diagnosis. IAFCM method gave the considerable classification accuracy among the other existing classifiers tested, it has not em...

This paper propose two decision fusion-based multitemporal classifiers, namely, the jointly likelihood and the weighted majority fusion classifiers, that are derived using two different definitions of the minimum expected cost. Without any overhead incurred by multitemporal processing, a user-selected conventional pixelwise classifier makes local class decisions separately using each temporal d...

Previously we proposed a scheme to generate fuzzy rule-based multiclassification systems by means of bagging, mutual information-based feature selection, and a multicriteria genetic algorithm (GA) for static component classifier selection guided by the ensemble training error. In the current contribution we extend the latter component by the use of two bi-criteria fitness functions, combining t...

Accurate, up-to-date and accessible information on the state of coral reef ecosystem is necessary for informed and effective management of these important marine resources. However, environments containing these habitats are challenging to map due to their remoteness, extent and costs of monitoring. In this research, the capabilities of satellite remote sensing techniques combined with in situ ...

The edited technique is of great importance in pattern recognition. The classical edited fuzzy technique use fuzzy k nearest neighbors(FKNN) to take out some useless samples which was classified erroneously in the editing process. In this paper, a proposed edited fuzzy k nearest neighbors based on threshold is developed, which not only consider the maximum membership value but also consider tha...