학술논문

Classifying coloured objects under different lighting conditions using the HSV colour model and a neural network
Document Type
Conference
Source
1999 European Control Conference (ECC) Control Conference (ECC), 1999 European. :3975-3981 Aug, 1999
Subject
Robotics and Control Systems
Power, Energy and Industry Applications
Signal Processing and Analysis
Transportation
Image color analysis
Training
Lighting
Biological neural networks
Object recognition
Cameras
Colour
Object Recognition
Neural Networks
Language
Abstract
This paper reports on the results obtained when using Radial Basis Neural Networks to classify different objects using only colour data extracted from images captured under different lighting conditions. Each network is trained with data from a single image and then tested with data from images containing the same collection of objects, but captured under different lighting conditions. The ability of the neural networks to generalize is tested to see how well it can recognise the objects when the ambient light source is changed. Results relating to the classification success of each of the networks are presented.