Image retrieval: Color and texture combining based on query-image

7Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

Abstract

It is a common way to process different image features independently in order to measure similarity between images. Color and texture are the common ones to use for searching in natural images. In [10] a technique to combine color and texture features based on a particular query-image in order to improve retrieval efficiency was proposed. Weighted linear combination of color and texture metrics was considered as a mixed-metrics. In this paper the mixed-metrics with different weights are compared to pure color and texture metrics and widely used CombMNZ data fusion algorithm. Experiments show that proposed metrics outperform CombMNZ method in some cases, and have close results in others. © 2008 Springer-Verlag.

References Powered by Scopus

Color indexing

4732Citations
922Readers
Get full text

Texture features for browsing and retrieval of image data

3208Citations
742Readers
Get full text

Analyses of multiple evidence combination

480Citations
83Readers
Get full text

Cited by Powered by Scopus

Image analysis and compression: Renewed focus on texture

17Citations
25Readers

Effective and efficient subjective testing of texture similarity metrics

11Citations
15Readers
Get full text

Image retrieval based on multi-feature similarity score fusion using genetic algorithm

6Citations
9Readers
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Markov, I., & Vassilieva, N. (2008). Image retrieval: Color and texture combining based on query-image. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5099 LNCS, pp. 430–438). https://doi.org/10.1007/978-3-540-69905-7_49

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 2

50%

Professor / Associate Prof. 1

25%

Researcher 1

25%

Readers' Discipline

Tooltip

Computer Science 4

80%

Engineering 1

20%

Save time finding and organizing research with Mendeley

Sign up for free