Number Recognition Using Inductive Learning on Spiral Architecture

Xiangjian He, Tom Hintz, Qiang Wu, Lihong Zheng

Research output: Book chapter/Published conference paperConference paper

2 Citations (Scopus)
4 Downloads (Pure)

Abstract

In this paper, a number recognition algorithm on Spiral Architectureis proposed. This algorithm employs RULES-3 inductive learning method and template matching technique. The algorithm starts from a collection of samples of numbers from number plates. Edge maps of the samples are then detected based on Spiral Architecture. A set of rules are extracted using these samples by RULES-3. The rules describe the frequencies of 9 different edge masks appearing in the samples. Each mask is a cluster of 7 hexagonal pixels. In order to recognize a number plate, all numbers are tested one by one using the extracted rules. The number recognition is achieved by counting the frequencies of the 9 masks.
Original languageEnglish
Title of host publicationInternational Conference On Computer Vision (VISION'05)
EditorsHamid R Arabnia
Place of PublicationU.S.A
PublisherCSREA Press
Pages58-64
Number of pages7
ISBN (Electronic)1932415653
Publication statusPublished - 2005
EventInternational Conference on Computer Vision - Las Vegas, USA, New Zealand
Duration: 20 Jun 200523 Jun 2005

Conference

ConferenceInternational Conference on Computer Vision
CountryNew Zealand
Period20/06/0523/06/05

Fingerprint Dive into the research topics of 'Number Recognition Using Inductive Learning on Spiral Architecture'. Together they form a unique fingerprint.

Cite this