Force histograms and radial density for invariant image retrieval

P. Phokharatkul; N. Songneam; C. Kimpan; S. Phaiboon

doi:10.1115/1.802977.paper11

Force histograms and radial density for invariant image retrieval

P. Phokharatkul
, N. Songneam
, C. Kimpan
, S. Phaiboon

Department of Computer Engineering

Rangsit University
Mahidol University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In Content-Based Image Retrieval (CBIR), indexing techniques based on global features that relate color and texture are commonly used to represent a description of images. However this approach is unable to capture local information of parts of the image that contain different characteristics. Therefore, some necessary local features of image may be might do not taking in account. This research introduces the new methods in which using the force histograms and radial density to capture some invariant local features. The results show that the force histograms and radial density use to solve the problem caused by variations in scaling, rotation, and translation. Furthermore this technique provides that efficient features to retrieve the sought image where difference pattern of objects may affect the retrieval accuracy.

Original language	English
Title of host publication	ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering
Publisher	American Society of Mechanical Engineers (ASME)
Pages	95-102
Number of pages	8
ISBN (Print)	9780791802977
DOIs	https://doi.org/10.1115/1.802977.paper11
Publication status	Published - 2009

Publication series

Name	ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering
Volume	1

Keywords

Force histograms
Invariant image retrieval
Radial density

Access to Document

10.1115/1.802977.paper11

Cite this

Phokharatkul, P., Songneam, N., Kimpan, C., & Phaiboon, S. (2009). Force histograms and radial density for invariant image retrieval. In ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering (pp. 95-102). (ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering; Vol. 1). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/1.802977.paper11

Phokharatkul, P. ; Songneam, N. ; Kimpan, C. et al. / Force histograms and radial density for invariant image retrieval. ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering. American Society of Mechanical Engineers (ASME), 2009. pp. 95-102 (ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering).

@inproceedings{eee44c299e6846c4aa5ae952e6c51faa,

title = "Force histograms and radial density for invariant image retrieval",

abstract = "In Content-Based Image Retrieval (CBIR), indexing techniques based on global features that relate color and texture are commonly used to represent a description of images. However this approach is unable to capture local information of parts of the image that contain different characteristics. Therefore, some necessary local features of image may be might do not taking in account. This research introduces the new methods in which using the force histograms and radial density to capture some invariant local features. The results show that the force histograms and radial density use to solve the problem caused by variations in scaling, rotation, and translation. Furthermore this technique provides that efficient features to retrieve the sought image where difference pattern of objects may affect the retrieval accuracy.",

keywords = "Force histograms, Invariant image retrieval, Radial density",

author = "P. Phokharatkul and N. Songneam and C. Kimpan and S. Phaiboon",

year = "2009",

doi = "10.1115/1.802977.paper11",

language = "English",

isbn = "9780791802977",

series = "ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering",

publisher = "American Society of Mechanical Engineers (ASME)",

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booktitle = "ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering",

}

Phokharatkul, P, Songneam, N, Kimpan, C & Phaiboon, S 2009, Force histograms and radial density for invariant image retrieval. in ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering. ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering, vol. 1, American Society of Mechanical Engineers (ASME), pp. 95-102. https://doi.org/10.1115/1.802977.paper11

Force histograms and radial density for invariant image retrieval. / Phokharatkul, P.; Songneam, N.; Kimpan, C. et al.
ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering. American Society of Mechanical Engineers (ASME), 2009. p. 95-102 (ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Force histograms and radial density for invariant image retrieval

AU - Phokharatkul, P.

AU - Songneam, N.

AU - Kimpan, C.

AU - Phaiboon, S.

PY - 2009

Y1 - 2009

N2 - In Content-Based Image Retrieval (CBIR), indexing techniques based on global features that relate color and texture are commonly used to represent a description of images. However this approach is unable to capture local information of parts of the image that contain different characteristics. Therefore, some necessary local features of image may be might do not taking in account. This research introduces the new methods in which using the force histograms and radial density to capture some invariant local features. The results show that the force histograms and radial density use to solve the problem caused by variations in scaling, rotation, and translation. Furthermore this technique provides that efficient features to retrieve the sought image where difference pattern of objects may affect the retrieval accuracy.

AB - In Content-Based Image Retrieval (CBIR), indexing techniques based on global features that relate color and texture are commonly used to represent a description of images. However this approach is unable to capture local information of parts of the image that contain different characteristics. Therefore, some necessary local features of image may be might do not taking in account. This research introduces the new methods in which using the force histograms and radial density to capture some invariant local features. The results show that the force histograms and radial density use to solve the problem caused by variations in scaling, rotation, and translation. Furthermore this technique provides that efficient features to retrieve the sought image where difference pattern of objects may affect the retrieval accuracy.

KW - Force histograms

KW - Invariant image retrieval

KW - Radial density

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DO - 10.1115/1.802977.paper11

M3 - Conference contribution

AN - SCOPUS:78649293463

SN - 9780791802977

T3 - ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering

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BT - ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering

PB - American Society of Mechanical Engineers (ASME)

ER -

Phokharatkul P, Songneam N, Kimpan C, Phaiboon S. Force histograms and radial density for invariant image retrieval. In ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering. American Society of Mechanical Engineers (ASME). 2009. p. 95-102. (ICACTE 2009 - Proceedings of the 2nd International Conference on Advanced Computer Theory and Engineering). doi: 10.1115/1.802977.paper11

Force histograms and radial density for invariant image retrieval

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