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Bio-medical Ontologies Maintenance and Change Management

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96 L. Stanescu, D. Dan Burdescu, <strong>and</strong> M. Brezovan<br />

2<br />

( R − G)<br />

l1(<br />

R,<br />

G,<br />

B)<br />

=<br />

2<br />

2<br />

2<br />

( R − G)<br />

+ ( R − B)<br />

+ ( G − B)<br />

2<br />

( G − B)<br />

l3(<br />

R,<br />

G,<br />

B)<br />

=<br />

2<br />

2<br />

2<br />

( R −G)<br />

+ ( R − B)<br />

+ ( G − B)<br />

2<br />

( G − B)<br />

l3(<br />

R,<br />

G,<br />

B)<br />

=<br />

2<br />

2<br />

2<br />

( R − G)<br />

+ ( R − B)<br />

+ ( G − B)<br />

(3.12)<br />

Its characteristics are [28, 80]: nonlinear transformation, H is independent on<br />

viewing direction, object geometry, direction <strong>and</strong> intensity of the illumination <strong>and</strong><br />

highlights.<br />

3.5 The Representation of the Color Features<br />

3.5.1 Color Histograms<br />

Indexing images by global color distribution has been achieved by using color histograms.<br />

For example, an image that contains different levels of grey can be transformed<br />

in a histogram that defines the number of pixels of each color (level of<br />

grey). For the color images, the color histograms can have a dimension higher than<br />

2, because the colors are represented as arrays with three components [18, 86].<br />

For a specific image there is only one histogram, but different images might<br />

have identical histograms. Swain <strong>and</strong> Ballard confirmed that histograms are<br />

invariant to translations, rotations <strong>and</strong> they are slightly variant when the viewing<br />

angle or the scale is changed, but when the image is transformed in the histogram,<br />

spatial information is lost. Color histograms can be considered a good solution for<br />

comparing images in content-based visual query.<br />

The next definition can be given [86]:<br />

The distribution of colors in an image, region or object is represented by a<br />

histogram.<br />

Having an image I[x,y] with three color channels I = (I R ,I G ,I B ), the histogram is<br />

given by:<br />

∑∑<br />

− X 1 Y −1<br />

1,<br />

if : Qc<br />

( Tc<br />

I[<br />

x,<br />

y])<br />

= m<br />

h c [ m]<br />

= ⎨⎧ (3.13)<br />

0,<br />

otherwise<br />

x = 0 y = 0 ⎩<br />

Where X, Y represent the width <strong>and</strong> the height of the image.<br />

In the content-based retrieval process, the histograms are normalized. This<br />

process is necessary to make the histograms <strong>and</strong> image matching invariant to<br />

image size.<br />

3.5.2 Binary Color Sets<br />

The images or regions color content can be represented more compact with the<br />

binary color sets. J.R. Smith <strong>and</strong> Shih-Fu Chang introduced this solution at the

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