| Summary: | 碩士 === 元智大學 === 電資與資訊工程研究所 === 86 === In this study, we propose a genetic algorithm for image segmentation on a linked regular pyramid with connectivity preserving. The hierarchy of pyramid is placed into a GA processing for evolution. Since the genetic algorithms always provide global optimal solutions and pyramid algorithms support fast parallel processing for multiresolution image
analysis, near-optimal multiresolution segmentation results
can be obtained. Some attributes of irregular pyramid, such
as clustering and connectivity preserving relinking, are also
involved in our regular hierarchy to construct a simple and
powerful computational structure. Since GA evolution makes the
parent values and child-parent links computation reach
near-optimal result, a more efficient pyramid data can be
obtained. Consequently, these pyramid data can be used to
produce the multiresolution segmentation results. Moreover,
some novel ideas are also proposed in this study. First, the
chromosome sizes dependent on level sizes are used to
facilitate the GA evolution on each level. Then, an adaptable
candidate parent window is used to obtain different segmented
results. In general, small window leads to compact connected
segment, while large window leads to fine
(sometimes scattered) connected segment. Experimental results
prove the effectiveness, robustness and feasibility of our
algorithm.
|
|---|
