Backpropagation Neural Network For Colour Recognition
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...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
2002
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/12083/1/FK_2002_49_A.pdf |
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| Summary: | 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. |
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