Title :
Stochastic search approach to object location
Author :
Cohen, Harvey A. ; Harvey, Alan L.
Author_Institution :
Dept. of Comput. Sci. & Comput. Eng., La Trobe Univ., Melbourne, Vic., Australia
Abstract :
Object location within an image involves establishing a location within an image for which a particular error function is minimised, and thus is essentially an optimization problem. Within the content of location via template matching, a random search approach, called a cluster search, based on an extension of mathematical methods due to Matyas has been studied to determine the most appropriate parameter β. For well chosen β the cluster search has been shown to be on average significantly faster than the fastest deterministic search schemes, notably coarse fine approaches
Keywords :
computer vision; image matching; object recognition; search problems; stochastic processes; Matyas algorithm; cluster search; coarse fine approaches; grey scale template; image procesing; object location; optimization; random search; stochastic search; template matching; Australia; Character recognition; Computer errors; Computer science; Convergence; Image coding; Image recognition; Machine vision; Shape; Stochastic processes;
Conference_Titel :
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2129-4
DOI :
10.1109/ICSMC.1994.400197
