Curvelet-Based Texture Description to Classify Intact and Damaged Boar Spermatozoa View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2012

AUTHORS

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

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). More... »

PAGES

448-455

References to SciGraph publications

Book

TITLE

Image Analysis and Recognition

ISBN

978-3-642-31297-7
978-3-642-31298-4

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-31298-4_53

DOI

http://dx.doi.org/10.1007/978-3-642-31298-4_53

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1048323198


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