Backpropagation Neural Network For Colour Recognition

AL-Naqeeb, Abdul Aziz Hussien (2002) Backpropagation Neural Network For Colour Recognition. Masters thesis, Universiti Putra Malaysia.

[img] PDF
1305Kb

Abstract

Colour Image Processing (CIP) is useful for inspection system and Automatic Packing Lines Systems. CIP usually needs expensive and special hardware as well as software to extract colour from image. Most of CIP software use statistical methods to extract colours and some system use Neural Network such as Counter-Propagation and Back-Propagation . Some researchers had used Neural Network methods to recognize colour of Commission Internationale de L'Ec1airage (CIE) Models either L *u *v or L *a *b. CIE colour components need special and expensive devices to extract their values from an image. However, this project will use RED, GREEN, BLUE (RGB) colour components, which can be read from an image. In this research, RGB values are used to represent the colour. RGB values are used in two forms. The first form is the actual values that are used in PPM File Format within (0,255) and the second form is normalized RGB values within (0, I ). Back-Propagation Neural Network is used to recognize colour in RGB values. It is found that RGB is useful when used with Neural Network and the Normalized RGB value is faster in the learning of neural network.

Item Type:Thesis (Masters)
Subject:Image processing
Chairman Supervisor:Abdul Rahman Ramli, PhD
Call Number:FK 2002 49
Faculty or Institute:Faculty of Engineering
ID Code:12083
Deposited By: Mohd Nezeri Mohamad
Deposited On:18 Jul 2011 02:14
Last Modified:18 Jul 2011 02:14

Repository Staff Only: Edit item detail

Document Download Statistics

This item has been downloaded for since 18 Jul 2011 02:14.

View statistics for "Backpropagation Neural Network For Colour Recognition "


Universiti Putra Malaysia Institutional Repository

Universiti Putra Malaysia Institutional Repository is an on-line digital archive that serves as a central collection and storage of scientific information and research at the Universiti Putra Malaysia.

Currently, the collections deposited in the IR consists of Master and PhD theses, Master and PhD Project Report, Journal Articles, Journal Bulletins, Conference Papers, UPM News, Newspaper Cuttings, Patents and Inaugural Lectures.

As the policy of the university does not permit users to view thesis in full text, access is only given to the first 24 pages only.