Feature extraction implementation for handwritten numeral recognition

Author

• Prashanth K. Banuru

Author Type

Graduate Student

Date of Award

1994

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Shankar, Ravi

Abstract

Feature extraction for handwritten character recognition has always been a challenging problem for investigators in the field. The problem gets worse due to large variations present for each type of input character. Our algorithm computes directional features for alphanumeric input mapped on to a hexagonal lattice. The algorithm implements size and scale invariance that is a requirement for achieving a reasonably good recognition rate. Functional performance has been verified for an hexagonal lattice mapped input on the data obtained from the US postal service handwritten character database. In this thesis, we implemented the algorithm in a Xilinx FPGA (XC4xxx series).

Extent

155 p.

Comments

College of Engineering and Computer Science|FAU Electronic Theses and Dissertations Collection|Thesis (M.S.)--Florida Atlantic University, 1994.|College of Engineering and Computer Science

Recommended Citation

Banuru, Prashanth K., "Feature extraction implementation for handwritten numeral recognition" (1994). Electronic Theses and Dissertations 1990 - 1999. 589.
https://digitalcommons.fau.edu/etd_general_4/589

Identifier

FADT15103

Format

pdf