Document Type
Article
Date
1997
Keywords
Shape matching, Pattern recognition, Simulation annealing, Genetic algorithms, Attributed strings, Evolutionary computing
Language
English
Disciplines
Computer Sciences
Description/Abstract
Partial shape matching may be viewed as an optimization problem, to be solved using methods such as simulated annealing (SA) and genetic algorithms (GAs). We apply and compare both these methods for matching input shapes with model shapes described in terms of features such as line segments and angles. The quality of matching is gauged using a measure derived from attributed shape grammars [10, 11]. Current results show that both SA and GA succeed in the shape matching task; the GA is faster and yields the global optimum more often than the versions of SA implemented.
Recommended Citation
Ozcan, Ender and Mohan, Chilukuri K., "Simulated annealing and genetic algorithms for partial shape matching" (1997). Electrical Engineering and Computer Science - All Scholarship. 141.
https://surface.syr.edu/eecs/141
