COLOR IMAGE IDENTIFICATION BASED ON 2-D POWER SPECTRUM BASED ON NEURAL NETWORK

Hassan J. Hassan, M.Sc.

	COLOR IMAGE IDENTIFICATION BASED ON 2-D POWER SPECTRUM BASED ON NEURAL NETWORK
IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING
Article 1, Volume 7, Issue 1, 2007, Pages 74-86
Author
M.Sc. Hassan J. Hassan
Abstract
Abstract: Image identification plays a great role in industrial, remote sensing, and military applications. It is concerned with the generation of a signature to the image. This work proposes a dynamic program (use Neural Network) to identify the color image depending on the distribution of the monochrome colors (red, green, and blue) in the same image to make image signature accordingly, which is represented by a values named power spectrum. The first step is to analyze the three-band monochrome image (color image) to Red, Green and Blue image, then deal with each image as a grey scale one which is represented as a 2-D matrix. The second step is to make Fourier Transform to each grey scale image in order to extract the implicit information in that image. The calculations of 2- D Power Spectrum for each image have been done to construct the final feature vector for each one. Finally, in the third step, and in order to handle problems of large input dimensions, a multilayer perceptron Neural Network has been used with two hidden layers. The input of the Neural Network structure is the final feature vectors which are obtained from the previous step. All programs are written using MATLAP VER. 6.5 programming language.
Keywords
Image Recognition; neural network; Transformation Technique; Texture Classification

Full Text

Statistics Article View: 382 PDF Download: 21