Title
Boar spermatozoa classification using longitudinal and transversal profiles (LTP) descriptor in digital images
Abstract
A new textural descriptor, named Longitudinal and Transversal Profiles (LTP), has been proposed. This descriptor was used to classify 376 images of dead spermatozoa heads and 472 images of alive ones. The result obtained with this descriptor has been compared with the Pattern spectrum, Flusser, Hu, and a descriptor based on statistical values of the histogram. The features vectors computed have been classified using a back-propagation Neural Network and the kNN (k Nearest Neighbours) algorithm. Classification error obtained with LTP was 30.58% outperforming the other descriptors. The area under the ROC curve (AUC) has also been calculated confirming that the performance of the proposed descriptor is better that of the other texture descriptors.
Year
DOI
Venue
2011
10.1007/978-3-642-21073-0_36
IWCIA
Keywords
Field
DocType
proposed descriptor,digital image,texture descriptors,pattern spectrum,boar spermatozoa classification,roc curve,classification error,back-propagation neural network,k nearest neighbours,transversal profiles,dead spermatozoa head,transversal profile,new textural descriptor,feature vector,spectrum
Computer vision,Histogram,Pattern recognition,Local binary patterns,Transversal (geometry),Digital image,Pattern spectrum,Digital image analysis,Artificial intelligence,Area under the roc curve,Artificial neural network,Mathematics
Conference
Volume
ISSN
Citations 
6636
0302-9743
6
PageRank 
References 
Authors
0.53
5
4
Name
Order
Citations
PageRank
Enrique Alegre113921.84
Oscar García-Olalla2424.24
Víctor González-Castro39010.70
Swapna Joshi4283.18