Bio-medical Ontologies Maintenance and Change Management

Multimedia Medical Databases 127
back-projection algorithm for each set c is applied and the color regions
are found. For each region the local histogram Ln [m] is recorded.
– The residue histogram [ m]
= H[
m]
− ∑ L [ m]
is updated.
H r
n n
3. Detection of the three colors regions…
Next, two implementations of the color set back-projection algorithm will be presented.
These original implementations were designed at Software Engineering
Department, Faculty of Automation, Computers and Electronics, Craiova.
In the first implementation of the color set back-projection algorithm (Method
1), the image is transformed in HSV color system and quantized to 166 colors. At
the end of this process, both the global histogram of the image and the color set
are available. To the matrix that stores only the quantized colors from 0 to 165 it is
applied a 5x5 median filter, which has the role of to eliminate the isolated points.
Having the HSV quantized matrix it is possible to begin the process of regions
extraction presented above. It may be observed that this process it is in fact a
depth–first traversal, described in pseudo-cod in the following way:
procedure FindRegions (Image I, colorset C)
InitStack(S)
Visited = ∅
for *each node P in the I do
if *color of P is in C then
PUSH(P)
Visited ← Visited ∪ {P}
while not Empty(S) do
CrtPoint