Application of fuzzy theory to pattern recognition

Author

David Usechak, New Jersey Institute of Technology

Document Type

Dissertation

Date of Award

Spring 5-31-1983

Degree Name

Doctor of Engineering Science in Electrical Engineering

Department

Electrical Engineering

First Advisor

Stanley S. Reisman

Second Advisor

Denis L. Blackmore

Third Advisor

Joseph Frank

Fourth Advisor

Sol Rosenstark

Abstract

Piecewise curve approximation is used to describe boundaries of objects in pictures and waveforms. The method consists of linear and quadratic piecewise polynomial approximations in which the error must not exceed a predetermined cost threshold. A fuzzy Bayes model is used to determine if a breakpoint exists within an interval I_n or between intervals I_n and I_n+1 and to determine whether these intervals can be merged for data compaction reasons. In order to achieve these objectives a new fast algorithm has been proposed which gives good curve/object fitting. This algorithm uses a technique for generating generalized inverse matrices once an initial generalized inverse matrix has been determined. The continuity requirements at the breakpoints are relaxed such that the only requirement is that the data point for interval I_n-1 is the starting point for interval I_n. Results of computer experiments with graphic outlines and radar data are reported.

Recommended Citation

Usechak, David, "Application of fuzzy theory to pattern recognition" (1983). Dissertations. 1279.
https://digitalcommons.njit.edu/dissertations/1279