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Colour differentiation in digitial images

Shen, Zhenliang (2003) Colour differentiation in digitial images. Research Master thesis, Victoria University of Technology.

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Abstract

To measure the quality of green vegetables in digital images, the colour appearance of the vegetable is one of the main factors. In general, green colour represents good quality and yellow colour represents poor quality empirically for green-vegetable. The colour appearance is mainly determined by its hue, however, the value of brightness and saturation affects the colour appearance under certain conditions. To measure the colour difference between green and yellow, a series of experiments have been designed to measure the colour difference under varying conditions. Five people were asked to measure the colour differences in different experiments. First, colour differences are measured as two of the values hue, brightness, and saturation are kept constant. Then, the previous results are applied to measure the colour difference as one of the values hue, brightness, and saturation is kept constant. Lastly, we develop a colour difference model from the different values of hue, brightness, and saturation. Such a colour difference model classifies the colours between green and yellow. A windows application is designed to measure the quality of leafy vegetables by using the colour difference model. The colours of such vegetables are classified to represent different qualities. The measurement by computer analysis conforms to that produced by human inspection.

Item Type: Thesis (Research Master thesis)
Additional Information:

This thesis is presented in fulfillment of the requirements
for the degree of Master of Science

Uncontrolled Keywords: colour differentiation, digital images, colour difference model, green vegetables
Subjects: FOR Classification > 0801 Artificial Intelligence and Image Processing
Faculty/School/Research Centre/Department > School of Engineering and Science
Depositing User: VU Library
Date Deposited: 23 Jun 2010 03:38
Last Modified: 23 May 2013 16:42
URI: http://vuir.vu.edu.au/id/eprint/15529
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