Acrosome integrity classification of boar spermatozoon images using DWT and texture descriptors

Proceedings of VIPIMAGE 2007 - 1st ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing

Volumn , Issue , 2008, Pages 165-168

  González, Maribel ^a   Alegre, Enrique ^a   Alaiz, Rocío ^a   Sánchez, Lidia ^b  

^a Department of Electrical Systems and Automatic Engineering

^b UNIVERSITY OF LEÓN   (Spain)

Author keywords

Backpropagation; Boar semen; Discrete wavelet transform; Neural networks

Indexed keywords

BACKPROPAGATION; BODY FLUIDS; DISCRETE WAVELET TRANSFORMS; IMAGE PROCESSING; IMAGING SYSTEMS; TEXTURES;

ACTIVATION FUNCTIONS; AUTOMATIC ASSESSMENTS; BOAR SEMEN; CO-OCCURRENCE MATRICES; FIRST-ORDER STATISTICS; HIDDEN LAYERS; MULTI-LAYER PERCEPTRON NETWORKS; SECOND ORDERS; STANDARD DEVIATIONS; STATISTICAL DESCRIPTORS; SUBBANDS; TEXTURE DESCRIPTORS; TEXTURE FEATURES;

NEURAL NETWORKS;

EID: 60749135281     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. J. Verstegen, M. Iguer-Ouada, and K. Onclin. Computer assisted semen analyzers in andrology research and veterinary practice. Theriogenology, 57:149-179, 2002.
2. C. Linneberg, P. Salamon, C. Svarer, and L.K. Hansen. Towards semen quality assessment using neural networks. In Proc. IEEE Neural Networks for Signal Processing IV, pages 509-517, 1994.
3. L. Sanchez, N. Petkov, and E. Alegre. Statistical approach to boar semen head classification based on intracellular intensity distribution. In A. Gagalowicz and W. Philips, editors, Proc. Int. Conf. on Computer Analysis of Images and Patterns, CAIP 2005, Lecture Notes in Computer Science, volume 3691, pages 88-95. Springer-Verlag Berlin Heidelberg, 2005.
4. L. Sanchez, N. Petkov, and E. Alegre. Classification of boar spermatozoid head images using a model intracellular density distribution. In M. Lazo and A. Sanfeliu, editors, Progress in Pattern Recognition, Image Analysis and Applications: Proc. 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Lecture Notes in Computer Science, volume 3773, pages 154-160. Springer-Verlag Berlin Heidelberg, 2005.
5. N. Petkov, E. Alegre, M. Biehl, and L. Sanchez. Lvq acrosome integrity assessment of boar sperm cells. CompIMAGES, Computational modelling of objects represented in images, 2006.
6. F. Albregtsen, H. Schulerud, and L. Yang. Texture classification of mouse liver cell nuclei using invariant moments of consistent regions. In Computer Analysis of Images and Patterns, pages 496-502, 1995.
7. D.M.U. Sabino, L. da Fontoura, E.G. Rizzatti, and M.A. Zago. A texture approach to leukocyte recognition. 10(4):205-216, August 2004.
8. T. Alvarez, Y. Martin, S. Perez, F. Santos, F. Tadeo, S. Gonzalez, J. Arribas, and P. Vega. Classification of microorganisms using image processing techniques, pages I: 329-332, 2001.
9. S. Arivazhagan and L. Ganesan. Texture classification using wavelet transform. Pattern Recognition Letters, 24(9-10): 1513-1521, June 2003.
10. R. Masuoka. Neural networks learning differential data. Master's thesis, Department of Mathematical Sciences, The University of Tokyo, March 2000.
11. L. Sanchez, N. Petkov, and E. Alegre. Statistical approach to boar semen evaluation using intracellular intensity distribution of head images. Cellular and Molecular Biology, 52(6):38-43, 2006.
12. R.M. Haralick. Statistical and structural approaches to texture. In Proceedings of the IEEE, pages 45-69, 1978.