How to make a query in image retrieval with partial information extracted from multiple image samples?

Sheung Wai Chan, Yiu Ming Cheung*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review


The existing image retrieval methods generally require at least one complete image as a query sample. From the practical point of view, a user may not have an image sample in hand for query. Instead, partial information from multiple image samples would be available. This paper therefore attempts to deal with this problem by presenting a novel framework that allows a user to make an image query composed of several partial information extracted from multiple image samples via Boolean operations (i.e. AND, OR and NOT). Based on the request from the query, a Descriptor Cluster Label Table (DCLT) is designed to efficiently find out the result of Boolean operations on partial information. Experiments show the promising result of the proposed framework on commodity query and criminal investigation, respectively, although it is essentially applicable to different scenarios as well by changing descriptors.

Original languageEnglish
Article number2154021
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Issue number7
Early online date27 Mar 2021
Publication statusPublished - 15 Jun 2021

Scopus Subject Areas

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

User-Defined Keywords

  • Boolean operation
  • descriptor cluster label table
  • Example-based image retrieval
  • partial descriptor information


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