e-ISSN : 0975-4024 p-ISSN : 2319-8613   
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ABSTRACT

ISSN: 0975-4024

Title : Image mining and Automatic Feature extraction from Remotely Sensed Image (RSI) using Cubical Distance Methods
Authors : S.Sasikala, Dr.N.Radhakrishnan
Keywords : Image mining, Feature extraction, Cubical distance, Frequent Item set, Remote sensing Image
Issue Date : Apr-May 2013
Abstract :
Information processing and decision support system using image mining techniques is in advance drive with huge availability of remote sensing image (RSI). RSI describes inherent properties of objects by recording their natural reflectance in the electro-magnetic spectral (ems) region. Information on such objects could be gathered by their color properties or their spectral values in various ems range in the form of pixels. Present paper explains a method of such information extraction using cubical distance method and subsequent results. This method is one among the simpler in its approach and considers grouping of pixels on the basis of equal distance from a specified point in the image or selected pixel having definite attribute values (DN) in different spectral layers of the RSI. The color distance and the occurrence pixel distance play a vital role in determining similar objects as clusters aid in extracting features in the RSI domain.
Page(s) : 642-648
ISSN : 0975-4024
Source : Vol. 5, No.2