Image Processing Reference
In-Depth Information
Fig. 5.1
Task solving is finding a path from a problem to a solution
end. The resulting way can be a serpentine road or may even lead through a tunnel, if
enough effort is invested in its construction. Another possibility is to go through the
haunted swamps of heuristics. The path through the swamps seems to be rather easy
and straight-forward, as it is flat walking, but in fact it is neither smooth nor safe.
There might be unexpected turns and twists. There are few and badly marked paths
through these swamps. In case of even slight deviations the pioneer can easily find
himself at a dead end or even get sucked into the deadly waters. Only few researchers
find viable, elegant paths through the swamps. If it works out it may result in a shorter
way from problem to solution as compared to going on the high grounds of theory.
Using heuristics is often considered as a bad choice in the design of a visualization
algorithm. Reviewers of visualization papers tend to dislike heuristics. They comment
on heuristics like:
lots of parameter tweaking
,
only heuristics
,
yet another heuristic
,
too many heuristic choices
,or
ad hoc parameter specification
. Should we try to avoid
heuristics and attempt to only find the theoretically well-grounded solutions?
5.2 Heuristics
Heuristic (or heuristics; Greek: “
E
”, meaning
to find
or
to discover
) refers
to experience-based techniques for problem solving, learning, and discovering. As
an adjective, heuristic pertains to the process of gaining knowledge or some desired
result by intelligent guesswork rather than by following some pre-established rules,
laws, or formulae. The underlying theory might not even be known. Humans often
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