Curvelet-based texture description to classify intact and damaged boar spermatozoa

Víctor González-Castro; Enrique Alegre; Oscar García-Olalla; Diego García-Ordás; María Teresa García-Ordás; Laura Fernández-Robles

doi:10.1007/978-3-642-31298-4_53

Curvelet-based texture description to classify intact and damaged boar spermatozoa

Víctor González-Castro^*, Enrique Alegre, Oscar García-Olalla, Diego García-Ordás, María Teresa García-Ordás, Laura Fernández-Robles

^*Corresponding author for this work

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

Abstract / Description of output

The assessment of boar sperm head images according to their acrosome status is a very important task in the veterinary field. Unfortunately it can only be performed manually, which is slow, non-objective and expensive. It is important to provide companies an automatic and reliable method to perform this task. In this paper a new method which uses texture descriptors based on the Curvelet Transform is proposed. Its performance has been compared with other texture descriptors based on the Wavelet transform, and also with moments based descriptors, as they seem to be successful for this problem. Texture descriptors performed better, and curvelet-based ones achieved the best hit rate (97%) and area under the ROC curve (0.99).

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	448-455
Number of pages	8
Volume	7325 LNCS
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-31298-4_53
Publication status	Published - 27 Jul 2012
Externally published	Yes
Event	9th International Conference on Image Analysis and Recognition, ICIAR 2012 - Aveiro, United Kingdom Duration: 25 Jun 2012 → 27 Jun 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7325 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	9th International Conference on Image Analysis and Recognition, ICIAR 2012
Country/Territory	United Kingdom
City	Aveiro
Period	25/06/12 → 27/06/12

Keywords / Materials (for Non-textual outputs)

biomedical image
classification
Curvelet
feature extraction

Access to Document

10.1007/978-3-642-31298-4_53

Cite this

González-Castro, V., Alegre, E., García-Olalla, O., García-Ordás, D., García-Ordás, M. T., & Fernández-Robles, L. (2012). Curvelet-based texture description to classify intact and damaged boar spermatozoa. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 7325 LNCS, pp. 448-455). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7325 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-31298-4_53

González-Castro, Víctor ; Alegre, Enrique ; García-Olalla, Oscar et al. / Curvelet-based texture description to classify intact and damaged boar spermatozoa. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7325 LNCS PART 2. ed. 2012. pp. 448-455 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "Curvelet-based texture description to classify intact and damaged boar spermatozoa",

abstract = "The assessment of boar sperm head images according to their acrosome status is a very important task in the veterinary field. Unfortunately it can only be performed manually, which is slow, non-objective and expensive. It is important to provide companies an automatic and reliable method to perform this task. In this paper a new method which uses texture descriptors based on the Curvelet Transform is proposed. Its performance has been compared with other texture descriptors based on the Wavelet transform, and also with moments based descriptors, as they seem to be successful for this problem. Texture descriptors performed better, and curvelet-based ones achieved the best hit rate (97%) and area under the ROC curve (0.99).",

keywords = "biomedical image, classification, Curvelet, feature extraction",

author = "V{\'i}ctor Gonz{\'a}lez-Castro and Enrique Alegre and Oscar Garc{\'i}a-Olalla and Diego Garc{\'i}a-Ord{\'a}s and Garc{\'i}a-Ord{\'a}s, {Mar{\'i}a Teresa} and Laura Fern{\'a}ndez-Robles",

year = "2012",

month = jul,

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doi = "10.1007/978-3-642-31298-4_53",

language = "English",

isbn = "9783642312977",

volume = "7325 LNCS",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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González-Castro, V, Alegre, E, García-Olalla, O, García-Ordás, D, García-Ordás, MT & Fernández-Robles, L 2012, Curvelet-based texture description to classify intact and damaged boar spermatozoa. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 edn, vol. 7325 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7325 LNCS, pp. 448-455, 9th International Conference on Image Analysis and Recognition, ICIAR 2012, Aveiro, United Kingdom, 25/06/12. https://doi.org/10.1007/978-3-642-31298-4_53

Curvelet-based texture description to classify intact and damaged boar spermatozoa. / González-Castro, Víctor; Alegre, Enrique; García-Olalla, Oscar et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7325 LNCS PART 2. ed. 2012. p. 448-455 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7325 LNCS, No. PART 2).

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

TY - GEN

T1 - Curvelet-based texture description to classify intact and damaged boar spermatozoa

AU - González-Castro, Víctor

AU - Alegre, Enrique

AU - García-Olalla, Oscar

AU - García-Ordás, Diego

AU - García-Ordás, María Teresa

AU - Fernández-Robles, Laura

PY - 2012/7/27

Y1 - 2012/7/27

N2 - The assessment of boar sperm head images according to their acrosome status is a very important task in the veterinary field. Unfortunately it can only be performed manually, which is slow, non-objective and expensive. It is important to provide companies an automatic and reliable method to perform this task. In this paper a new method which uses texture descriptors based on the Curvelet Transform is proposed. Its performance has been compared with other texture descriptors based on the Wavelet transform, and also with moments based descriptors, as they seem to be successful for this problem. Texture descriptors performed better, and curvelet-based ones achieved the best hit rate (97%) and area under the ROC curve (0.99).

AB - The assessment of boar sperm head images according to their acrosome status is a very important task in the veterinary field. Unfortunately it can only be performed manually, which is slow, non-objective and expensive. It is important to provide companies an automatic and reliable method to perform this task. In this paper a new method which uses texture descriptors based on the Curvelet Transform is proposed. Its performance has been compared with other texture descriptors based on the Wavelet transform, and also with moments based descriptors, as they seem to be successful for this problem. Texture descriptors performed better, and curvelet-based ones achieved the best hit rate (97%) and area under the ROC curve (0.99).

KW - biomedical image

KW - classification

KW - Curvelet

KW - feature extraction

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U2 - 10.1007/978-3-642-31298-4_53

DO - 10.1007/978-3-642-31298-4_53

M3 - Conference contribution

AN - SCOPUS:84864130572

SN - 9783642312977

VL - 7325 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 448

EP - 455

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

T2 - 9th International Conference on Image Analysis and Recognition, ICIAR 2012

Y2 - 25 June 2012 through 27 June 2012

ER -

González-Castro V, Alegre E, García-Olalla O, García-Ordás D, García-Ordás MT, Fernández-Robles L. Curvelet-based texture description to classify intact and damaged boar spermatozoa. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). PART 2 ed. Vol. 7325 LNCS. 2012. p. 448-455. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-31298-4_53

Curvelet-based texture description to classify intact and damaged boar spermatozoa

Abstract / Description of output

Publication series

Conference

Keywords / Materials (for Non-textual outputs)

Access to Document

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Cite this