Motif correlogram for texture image retrieval

Atoany Nazareth Fierro-Radilla; Gustavo Calderon-Auza; Mariko Nakano-Miyatake; Héctor Manuel Pérez-Meana

doi:10.1007/978-3-319-22689-7_38

Motif correlogram for texture image retrieval

Atoany Nazareth Fierro-Radilla, Gustavo Calderon-Auza, Mariko Nakano-Miyatake, Héctor Manuel Pérez-Meana

Escuela Superior de Ingeniería Mecánica y Eléctrica (ESIME), Unidad Culhuacán

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

4 Scopus citations

Abstract

In this paper we present a novel, compact and effective method for extracting texture information from an image. We denominate this method as Motif Correlogram (MC), which computes the correlation between motif pairs of the same type. The proposed method was evaluated using different metrics commonly used in image retrieval, such as ARP (Average Retrieval Precision), ARR (Average Retrieval Rate) and ANMRR (Average Normalized Retrieval Rank). Also, the proposed scheme was compared with other texture descriptors, such as Steerable FIltres, Edge Histogram Descriptor (EHD) and two Co-occurrence Matrix-based algorithms: Motif Co-Occurrence Matrix (MCM) and Directional Local Motif XoR Patterns (DLMXoRP). The performance of the proposed method was evaluated using the Kylberg Dataset. The evaluation results show the proposed texture descriptor improves the texture image retrieval performance.

Original language	English
Title of host publication	Intelligent Software Methodologies, Tools and Techniques - 14th International Conference, SoMeT 2015, Proceedings
Editors	Hamido Fujita, Guido Guizzi
Publisher	Springer Verlag
Pages	496-505
Number of pages	10
ISBN (Print)	9783319226880
DOIs	https://doi.org/10.1007/978-3-319-22689-7_38
State	Published - 2015
Event	14th International Conference on New Trends in Intelligent Software Methodology, Tools, and Techniques, SoMeT 2015 - Naples, Italy Duration: 15 Sep 2015 → 17 Sep 2015

Publication series

Name	Communications in Computer and Information Science
Volume	532
ISSN (Print)	1865-0929

Conference

Conference	14th International Conference on New Trends in Intelligent Software Methodology, Tools, and Techniques, SoMeT 2015
Country/Territory	Italy
City	Naples
Period	15/09/15 → 17/09/15

Keywords

Co-occurrence matrix
Image retrieval
Motif correlogram matrix
Texture

Access to Document

10.1007/978-3-319-22689-7_38

Cite this

Fierro-Radilla, A. N., Calderon-Auza, G., Nakano-Miyatake, M., & Pérez-Meana, H. M. (2015). Motif correlogram for texture image retrieval. In H. Fujita, & G. Guizzi (Eds.), Intelligent Software Methodologies, Tools and Techniques - 14th International Conference, SoMeT 2015, Proceedings (pp. 496-505). (Communications in Computer and Information Science; Vol. 532). Springer Verlag. https://doi.org/10.1007/978-3-319-22689-7_38

Fierro-Radilla, Atoany Nazareth ; Calderon-Auza, Gustavo ; Nakano-Miyatake, Mariko et al. / Motif correlogram for texture image retrieval. Intelligent Software Methodologies, Tools and Techniques - 14th International Conference, SoMeT 2015, Proceedings. editor / Hamido Fujita ; Guido Guizzi. Springer Verlag, 2015. pp. 496-505 (Communications in Computer and Information Science).

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abstract = "In this paper we present a novel, compact and effective method for extracting texture information from an image. We denominate this method as Motif Correlogram (MC), which computes the correlation between motif pairs of the same type. The proposed method was evaluated using different metrics commonly used in image retrieval, such as ARP (Average Retrieval Precision), ARR (Average Retrieval Rate) and ANMRR (Average Normalized Retrieval Rank). Also, the proposed scheme was compared with other texture descriptors, such as Steerable FIltres, Edge Histogram Descriptor (EHD) and two Co-occurrence Matrix-based algorithms: Motif Co-Occurrence Matrix (MCM) and Directional Local Motif XoR Patterns (DLMXoRP). The performance of the proposed method was evaluated using the Kylberg Dataset. The evaluation results show the proposed texture descriptor improves the texture image retrieval performance.",

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Fierro-Radilla, AN, Calderon-Auza, G, Nakano-Miyatake, M & Pérez-Meana, HM 2015, Motif correlogram for texture image retrieval. in H Fujita & G Guizzi (eds), Intelligent Software Methodologies, Tools and Techniques - 14th International Conference, SoMeT 2015, Proceedings. Communications in Computer and Information Science, vol. 532, Springer Verlag, pp. 496-505, 14th International Conference on New Trends in Intelligent Software Methodology, Tools, and Techniques, SoMeT 2015, Naples, Italy, 15/09/15. https://doi.org/10.1007/978-3-319-22689-7_38

Motif correlogram for texture image retrieval. / Fierro-Radilla, Atoany Nazareth; Calderon-Auza, Gustavo; Nakano-Miyatake, Mariko et al.
Intelligent Software Methodologies, Tools and Techniques - 14th International Conference, SoMeT 2015, Proceedings. ed. / Hamido Fujita; Guido Guizzi. Springer Verlag, 2015. p. 496-505 (Communications in Computer and Information Science; Vol. 532).

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

TY - GEN

T1 - Motif correlogram for texture image retrieval

AU - Fierro-Radilla, Atoany Nazareth

AU - Calderon-Auza, Gustavo

AU - Nakano-Miyatake, Mariko

AU - Pérez-Meana, Héctor Manuel

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - In this paper we present a novel, compact and effective method for extracting texture information from an image. We denominate this method as Motif Correlogram (MC), which computes the correlation between motif pairs of the same type. The proposed method was evaluated using different metrics commonly used in image retrieval, such as ARP (Average Retrieval Precision), ARR (Average Retrieval Rate) and ANMRR (Average Normalized Retrieval Rank). Also, the proposed scheme was compared with other texture descriptors, such as Steerable FIltres, Edge Histogram Descriptor (EHD) and two Co-occurrence Matrix-based algorithms: Motif Co-Occurrence Matrix (MCM) and Directional Local Motif XoR Patterns (DLMXoRP). The performance of the proposed method was evaluated using the Kylberg Dataset. The evaluation results show the proposed texture descriptor improves the texture image retrieval performance.

AB - In this paper we present a novel, compact and effective method for extracting texture information from an image. We denominate this method as Motif Correlogram (MC), which computes the correlation between motif pairs of the same type. The proposed method was evaluated using different metrics commonly used in image retrieval, such as ARP (Average Retrieval Precision), ARR (Average Retrieval Rate) and ANMRR (Average Normalized Retrieval Rank). Also, the proposed scheme was compared with other texture descriptors, such as Steerable FIltres, Edge Histogram Descriptor (EHD) and two Co-occurrence Matrix-based algorithms: Motif Co-Occurrence Matrix (MCM) and Directional Local Motif XoR Patterns (DLMXoRP). The performance of the proposed method was evaluated using the Kylberg Dataset. The evaluation results show the proposed texture descriptor improves the texture image retrieval performance.

KW - Co-occurrence matrix

KW - Image retrieval

KW - Motif correlogram matrix

KW - Texture

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M3 - Contribución a la conferencia

SN - 9783319226880

T3 - Communications in Computer and Information Science

SP - 496

EP - 505

BT - Intelligent Software Methodologies, Tools and Techniques - 14th International Conference, SoMeT 2015, Proceedings

A2 - Fujita, Hamido

A2 - Guizzi, Guido

PB - Springer Verlag

T2 - 14th International Conference on New Trends in Intelligent Software Methodology, Tools, and Techniques, SoMeT 2015

Y2 - 15 September 2015 through 17 September 2015

ER -

Fierro-Radilla AN, Calderon-Auza G, Nakano-Miyatake M , Pérez-Meana HM. Motif correlogram for texture image retrieval. In Fujita H, Guizzi G, editors, Intelligent Software Methodologies, Tools and Techniques - 14th International Conference, SoMeT 2015, Proceedings. Springer Verlag. 2015. p. 496-505. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-22689-7_38

Motif correlogram for texture image retrieval

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