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

Authors:
Víctor González-Castro;Enrique Alegre;Oscar García-Olalla;Diego García-Ordás;María Teresa García-Ordás;Laura Fernández-Robles
Affiliations:
University of León, Spain;University of León, Spain;University of León, Spain;University of León, Spain;University of León, Spain;University of León, Spain
Venue:
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II
Year:
2012

Citing 5
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Assessment of acrosome state in boar spermatozoa heads using n-contours descriptor and RLVQ

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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).