title: Class-associative multiple target detection by use of fringe-adjusted joint transform correlation.
abstract: We propose a class-associative correlation filter based technique for detecting a class of objects consisting of dissimilar patterns. The fringe-adjusted joint transform correlation algorithm is utilized to enhance the correlation performance, thus ensuring a strong and equal correlation peak for each element of the selected class. For enhanced performance, an enhanced version of the fringe-adjusted filter is incorporated in the class-associative multiple target detection process. The feasibility of the proposed technique has been tested by computer simulation.
authors.affiliation: Department of Electrical and Computer Engineering, University of South Alabama, Mobile, Alabama 36688, USA.
authors.forename: M S
authors.initials: MS
authors.lastname: Alam
authors.forename: M M
authors.initials: MM
authors.lastname: Rahman