Cross-correlation and related techniques have dominated the Image
processing field since the early fifties. Conventional template
matching algorithm based on cross-correlation requires complex
calculation and large time for object detection, which makes
difficult to use them in real time applications. The shortcomings
of this class of image matching methods have caused a slow-down in
the development of operational automated correlation systems. In
the proposed book particle swarm optimization & its variants
based algorithm is used for detection of object in image.
Implementation of this algorithm reduces the time required for
object detection than conventional template matching algorithm.
Algorithm can detect object in less number of iteration & hence
less time & energy than the complexity of conventional template
matching. This feature makes the method capable for real time
implementation.
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