Irshad Khalil,Sami Ur Rahman,Samad Baseer,Adnan Khalil,Fakhre Alam,



Legendre Polynomials,Shifted Legendre Polynomials,Classification,MRI Images,Image Processing,


In this paper, we study the computational strategy for the implementation of orthogonal moments to two-dimensional images. Automatic and accurate classification of Magnetic Resonance Images is of importance for the interpretation and analysis of these images and for this purpose different techniques have been proposed.  In this paper, we present Legendre Polynomial and two different classification-based methods for the classification of normal and abnormal MRI Images. In the first step, we apply Legendre polynomial to extract features from MRI images. In the second stage, two classifiers have been used which are employed to classify these images as normal and abnormal images. The proposed method was tested on tests with 75 images in which 15 images belong to the normal category images and the remaining 60 are abnormal images. The result derived from the confusion matrix test yielded a classification accuracy of 100.0% for these images.


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