soil salinity has been a large problem in arid and semi arid regions. preparation of such maps is useful for natural resource managers. old methods of preparing such maps require a lot of time and cost. multi-spectral remotely sensed dates due to the broad vision and repeating of these imageries is suitable for provide saline soil maps. this investigation is conducted to provide saline soil map...

Proposed system has been developed to extract the optimal features from the breast tumors using Enhanced Cuckoo Search (ECS) and presented in this paper. The texture feature, intensity histogram feature, radial distance feature and shape features have been extracted and the optimal feature set has been obtained using ECS. The overall accuracy of a minimum distance classifier and k-Nearest Neigh...

This paper proposes a new metric, called Context Based Covariance, to capture contextual information intrinsic to multivariate data. Based on this concept, a minimum distance classifier is designed, and its applicability to the domain of supervised machine learning is discussed. The performance of the proposed metric is compared with conventional minimum distance classifiers based on Mahalanobi...

A pattern recognition system used for industrial inspection has to be highly reliable and fast. The reliability is essential for reducing the cost caused by incorrect decisions, while speed is necessary for real–time operation. In this paper we address the problem of inspecting optical media like Compact Disks and Digital Versatile Disks. Here, defective disks have to be identified during produ...

This paper deals with the problem of identifying the nature of noise in order to apply the most appropriate algorithm for de-noising. The key idea involves isolation of some representative noise samples and extraction of their features for noise identification. The isolation of the noise samples is achieved through application of filters. Statistical features are extracted and the minimum dista...

Choosing appropriate values for kernel parameters is one of the key problems in many kernel-based methods because the values of these parameters have significant impact on the performances of these methods. In this paper, a novel approach is proposed to learn the kernel parameters in kernel minimum distance (KMD) classifier, where the values of the kernel parameters are computed through optimiz...

This paper deals with accuracy improvement of handwritten character recognition by the GLVQ (generalized learning vector quantization). In literature , the way of combining the FDA (Fisher discriminant analysis) and the GLVQ was investigated and evaluated to be effective for handwritten Chinese character recognition employing the minimum Euclidian distance classifier. In this paper, the project...

This paper investigates the potential information provided to the user by the uncertainty measures applied to the possibility distributions associated with the spatial units of an IKONOS satellite image, generated by two fuzzy classifiers, based, respectively, on the Nearest Neighbour Classifier and the Minimum Distance to Means Classifier. The deviation of the geographic unit characteristics f...