The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	Application of geometric hashing techniques to retrieval of high dimensional objects in scientific databases
Author:	Lu, Joyce Ye
View Online:	njit-etd1997-072 (ix, 70 pages ~ 1.7 MB pdf)
Department:	Department of Computer and Information Science
Degree:	Master of Science
Program:	Computer Science
Document Type:	Thesis
Advisory Committee:	Wang, Jason T. L. (Committee chair) Ng, Peter A. (Committee member) Nakayama, Marvin K. (Committee member)
Date:	1997-01
Keywords:	Hashing (Computer science). Object-oriented programming (Computer science).
Availability:	Unrestricted
Abstract:	An approach to designing very fast algorithms for tackling the problem of approximate object matching in very large databases of high-dimensional objects is proposed. Given are a target object C and a database D containing information about a set of high-dimensional objects each of which is represented as a set of points. Our algorithms have an off-line object preprocessing (shape representation) phase and a recognition phase. The described algorithms determine those objects from D which are the closest to object C, according to delete or insert some points, move and rotation. All of these can be achieved very efficiently with the help of geometric hashing techniques. This scheme has been successfully applied to a real scientific database.