An effective content-based visual image retrieval system

Xiuqi Li, Shu Ching Chen, Mei-Ling Shyu, Borko Furht

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Citations (Scopus)

Abstract

In this paper, an effective content-based visual image retrieval system is presented. This system consists of two main components: visual content extraction and indexing, and query engine. Each image in the image database is represented by its visual features: color and spatial information. The system uses a color label histogram with only thirteen bins to extract the color information from an image in the image database. A unique unsupervised segmentation algorithm combined with the wavelet technique generates the spatial feature of an image automatically. The resulting feature vectors are relatively low in dimensions compared to those in other systems. The query engine employs a color filter and a spatial filter to dramatically reduce the search range. As a result, queue processing is speeded up. The experimental results demonstrate that our system is capable of retrieving images that belong to the same category.

Original languageEnglish
Title of host publicationProceedings - IEEE Computer Society's International Computer Software and Applications Conference
Pages914-919
Number of pages6
DOIs
StatePublished - Oct 16 2002
Event26th Annual International Computer Software and Applications Conference - Oxford, United Kingdom
Duration: Aug 26 2002Aug 29 2002

Other

Other26th Annual International Computer Software and Applications Conference
CountryUnited Kingdom
CityOxford
Period8/26/028/29/02

Fingerprint

Image retrieval
Color
Engines
Bins
Labels
Processing

Keywords

  • Content-based image retrieval
  • Multimedia systems

ASJC Scopus subject areas

  • Software

Cite this

Li, X., Chen, S. C., Shyu, M-L., & Furht, B. (2002). An effective content-based visual image retrieval system. In Proceedings - IEEE Computer Society's International Computer Software and Applications Conference (pp. 914-919) https://doi.org/10.1109/CMPSAC.2002.1045122

An effective content-based visual image retrieval system. / Li, Xiuqi; Chen, Shu Ching; Shyu, Mei-Ling; Furht, Borko.

Proceedings - IEEE Computer Society's International Computer Software and Applications Conference. 2002. p. 914-919.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Li, X, Chen, SC, Shyu, M-L & Furht, B 2002, An effective content-based visual image retrieval system. in Proceedings - IEEE Computer Society's International Computer Software and Applications Conference. pp. 914-919, 26th Annual International Computer Software and Applications Conference, Oxford, United Kingdom, 8/26/02. https://doi.org/10.1109/CMPSAC.2002.1045122
Li X, Chen SC, Shyu M-L, Furht B. An effective content-based visual image retrieval system. In Proceedings - IEEE Computer Society's International Computer Software and Applications Conference. 2002. p. 914-919 https://doi.org/10.1109/CMPSAC.2002.1045122
Li, Xiuqi ; Chen, Shu Ching ; Shyu, Mei-Ling ; Furht, Borko. / An effective content-based visual image retrieval system. Proceedings - IEEE Computer Society's International Computer Software and Applications Conference. 2002. pp. 914-919
@inproceedings{4873b8f02051448ea7525d089c6cb235,
title = "An effective content-based visual image retrieval system",
abstract = "In this paper, an effective content-based visual image retrieval system is presented. This system consists of two main components: visual content extraction and indexing, and query engine. Each image in the image database is represented by its visual features: color and spatial information. The system uses a color label histogram with only thirteen bins to extract the color information from an image in the image database. A unique unsupervised segmentation algorithm combined with the wavelet technique generates the spatial feature of an image automatically. The resulting feature vectors are relatively low in dimensions compared to those in other systems. The query engine employs a color filter and a spatial filter to dramatically reduce the search range. As a result, queue processing is speeded up. The experimental results demonstrate that our system is capable of retrieving images that belong to the same category.",
keywords = "Content-based image retrieval, Multimedia systems",
author = "Xiuqi Li and Chen, {Shu Ching} and Mei-Ling Shyu and Borko Furht",
year = "2002",
month = "10",
day = "16",
doi = "10.1109/CMPSAC.2002.1045122",
language = "English",
isbn = "0769517277",
pages = "914--919",
booktitle = "Proceedings - IEEE Computer Society's International Computer Software and Applications Conference",

}

TY - GEN

T1 - An effective content-based visual image retrieval system

AU - Li, Xiuqi

AU - Chen, Shu Ching

AU - Shyu, Mei-Ling

AU - Furht, Borko

PY - 2002/10/16

Y1 - 2002/10/16

N2 - In this paper, an effective content-based visual image retrieval system is presented. This system consists of two main components: visual content extraction and indexing, and query engine. Each image in the image database is represented by its visual features: color and spatial information. The system uses a color label histogram with only thirteen bins to extract the color information from an image in the image database. A unique unsupervised segmentation algorithm combined with the wavelet technique generates the spatial feature of an image automatically. The resulting feature vectors are relatively low in dimensions compared to those in other systems. The query engine employs a color filter and a spatial filter to dramatically reduce the search range. As a result, queue processing is speeded up. The experimental results demonstrate that our system is capable of retrieving images that belong to the same category.

AB - In this paper, an effective content-based visual image retrieval system is presented. This system consists of two main components: visual content extraction and indexing, and query engine. Each image in the image database is represented by its visual features: color and spatial information. The system uses a color label histogram with only thirteen bins to extract the color information from an image in the image database. A unique unsupervised segmentation algorithm combined with the wavelet technique generates the spatial feature of an image automatically. The resulting feature vectors are relatively low in dimensions compared to those in other systems. The query engine employs a color filter and a spatial filter to dramatically reduce the search range. As a result, queue processing is speeded up. The experimental results demonstrate that our system is capable of retrieving images that belong to the same category.

KW - Content-based image retrieval

KW - Multimedia systems

UR - http://www.scopus.com/inward/record.url?scp=0036386999&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036386999&partnerID=8YFLogxK

U2 - 10.1109/CMPSAC.2002.1045122

DO - 10.1109/CMPSAC.2002.1045122

M3 - Conference contribution

AN - SCOPUS:0036386999

SN - 0769517277

SP - 914

EP - 919

BT - Proceedings - IEEE Computer Society's International Computer Software and Applications Conference

ER -