A method for measuring the complexity of image databases

Author

Rao, Aibing ; Srihari, Rohini K. ; Zhu, Lei ; Zhang, Aidong

Author_Institution

Center for Document Anal. & Recognition, State Univ. of New York, Buffalo, NY, USA

Volume

4

Issue

2

fYear

2002

fDate

6/1/2002 12:00:00 AM

Firstpage

160

Lastpage

173

Abstract

We present a framework for measuring the complexity of image databases, which characterizes the databases for image retrieval. Motivated from the concept of text corpus perplexity, the complexity of image databases is formulated based on image database statistics and information theory. We propose a quantitative metric which can be used to measure the degree of difficulty to retrieve images based on contents of the database. This metric is independent of queries, hence, it is objective. Experiments on both synthetic and real-world images demonstrate that the proposed measurement is highly effective in quantitatively measuring the contents of image databases for content-based retrieval.

Keywords

content-based retrieval; entropy; feature extraction; image retrieval; visual databases; complexity measurement method; content-based retrieval; degree of difficulty; image databases; image retrieval; information theory; quantitative metric; real-world images; statistics; synthetic images; text corpus perplexity; Algorithm design and analysis; Chaos; Content based retrieval; Feature extraction; Humans; Image databases; Image retrieval; Information retrieval; Shape measurement; Testing;

fLanguage

English

Journal_Title

Multimedia, IEEE Transactions on

Publisher

ieee

ISSN

1520-9210

Type

jour

DOI

10.1109/TMM.2002.1017731

Filename

1017731