Skip to main navigation Skip to search Skip to main content

Combining matching scores in identification model

  • SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

The paper discusses a problem of combining recognition scores for different classes produced by one recognizer during one recognition attempt. This problem arises in identification problems which we define as 1:N classification problems with big or variable N. By using artificial example we show that intuitive solution of making identification decision based solely on the best matching score is frequently suboptimal. Paper presents reasons for such behavior, and draws parallels with score normalization technique used in speaker identification. Two examples of real life applications illustrate the possible benefits of properly combining recognition scores.

Original languageEnglish
Title of host publicationProceedings of the Eighth International Conference on Document Analysis and Recognition
Pages1151-1155
Number of pages5
DOIs
StatePublished - 2005
Event8th International Conference on Document Analysis and Recognition - Seoul, Korea, Republic of
Duration: Aug 31 2005Sep 1 2005

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume2005
ISSN (Print)1520-5363

Conference

Conference8th International Conference on Document Analysis and Recognition
Country/TerritoryKorea, Republic of
CitySeoul
Period08/31/0509/1/05

Fingerprint

Dive into the research topics of 'Combining matching scores in identification model'. Together they form a unique fingerprint.

Cite this