Measuring classification complexity of image databases: a novel approach

Author

Rahman, A.F.R. ; Fairhurst, M.C.

Author_Institution

Electron. Eng. Labs., Kent Univ., Canterbury, UK

fYear

1999

fDate

1999

Firstpage

893

Lastpage

897

Abstract

A novel approach for estimating classification complexities of various image databases holding similar types of data is proposed. A new measure indicating the relative complexity of classification for an image database has been defined in terms of the statistical similarities existing between various samples belonging to various classes in the database. The proposed measure has been applied to five widely available databases containing samples of handwritten and machine printed characters and has been found to be very accurate in predicting the relative classification complexity of these databases. The proposed complexity measure is completely generalised and is applicable to the assessment of the relative classification complexity of any image database relative to any other databases containing similar types of images

Keywords

image classification; image recognition; statistical analysis; visual databases; classification complexity measurement; complexity measure; handwritten characters; image databases; image recognition systems; machine printed characters; relative classification complexity; statistical similarities; Image databases; Image processing; Image recognition; Laboratories; Process design; Spatial databases; System testing; Target recognition; Terminology;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Analysis and Processing, 1999. Proceedings. International Conference on

Conference_Location

Venice

Print_ISBN

0-7695-0040-4

Type

conf

DOI

10.1109/ICIAP.1999.797708

Filename

797708