A new SVM-based architecture for object recognition in color underwater images with classification refinement by shape descriptors

2006 IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR

Volumn 2, Issue , 2006, Pages 327-332

  Gordan, M ^a   Dancea, O ^b   Stoian, I ^b   Georgakis, A ^c   Tsatos, O ^d  

^a TECHNICAL UNIVERSITY OF CLUJ NAPOCA   (Romania)

^b IPA R and D Institute for Automation   (Romania)

^c UMEÅ UNIVERSITY   (Sweden)

^d ALBIODATA SA Information Systems Consulting   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ANALYSIS; IMAGE CLASSIFICATION; OBJECT RECOGNITION;

APPLICATION SPECIFIC; CLASSIFICATION RATES; CLASSIFICATION RESULTS; FALSE ACCEPTANCE RATE; FALSE REJECTION RATE; IMAGE ANALYSIS ALGORITHMS; PRESSURE EQUALIZATION; PROPOSED ARCHITECTURES;

SUPPORT VECTOR MACHINES;

EID: 78349283307     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AQTR.2006.254654     Document Type: Conference Paper

References (16)

1. Chodorowski, A., Gustavsson T., Mattsson U., "Support vector machines for oral lesion classification", Proc. IEEE Int. Symp. on Biomedical Imaging, 2002, pp. 173-176
2. T.J. Terrillon, M. N. Shirazi, M. Sadek, H. Fukamachi, S. Akamatsu, "Invariant face detection with support vector machines", Proc.15th International Conference on Pattern Recognition, Barcelona, Spain, 2000, Vol. 4, pp. 210-217
3. I. Buciu, C. Kotropoulos, I. Pitas, "Combining support vector machines for accurate face detection", Proc. IEEE Int. Conf. Image Processing, Thessaloniki, Greece, 2001, pp. 1054-1057
4. M. Gordan, C. Miron, G. Tepes, S. Pop, "Application of Support Vector Machine Classifiers for Mouth Localization in Facial Images", Proc. of the Symposium on Electronics and Telecommunications, Timisoara, Romania, Sept. 2002
5. Gordan M., Miron C., Stoian I., Dancea O., Tepes G. "Speeding-up the SVM-Based color image classifiers by using vector quantization", 2004 IEEE-TTTC International Conference on Automation, Quality & Testing, Robotics AQTR 2004 (THETA 14), Cluj Napoca 13-15 may 2004, vol. 2, pp. 183-188, 2004
6. M. Blain, "A new generation of underwater robot almost ready to take the plunge", Recherche-Developement, Institut de Recherche d'Hydro-Quebec 14 (1): 3, 2001
7. J. Batlle, T. Nicosevici, R. Garcia, and M. Carreras, "ROV-aided dam inspection: Practical results," 6th IFAC Conference on Manoeuvring and Control of Marine Crafts (MCMC), pp. 309-312, Girona, Spain, 2003
8. A. Ortiz, M. Simó, G. Oliver, "A vision system for an underwater cable tracker", Machine Vision Applications, 13(3): 129-140, 2002
9. I. Stoian, P. Ungureanu, L. Miclea, M. Gordan, S. Ignat, P. Ridao, "Image Processing Applied to Hydro Plant Surveillance", 28-30 mai 2003, Proceedings of the 4th Workshop on European Scientific and Industrial Collaboration WESIC 2003, University of Miskolcz, Ungaria, ISBN 963 661 570 5, vol. II, pp. 389-396
10. Carlos M. Travieso, Jesús B Alonso, Miguel A. Ferrer, "Facial identification using transformed domain by SVM", in 38th IEEE International Carnahan Conference on security Technology, Albuquerque, New Mexico, pp. 321-324, October 11-14, 2004
11. Kashif M. Rajpoot, Nasir M. Rajpoot, "Wavelets and Support Vector Machines for Texture Classification", in Proceedings of 8th IEEEINMIC' 2004
12. Bernd Heisele, Thomas Serre, Sayan Mukherjee, Tomaso Poggio: "Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images". CVPR (2) 2001: 18-24
13. V. N. Vapnik, Statistical Learning Theory, J. Wiley, N.Y., 1998
14. Bezdek, J. C., Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York, 1981
15. I. Pitas, Digital Image Processing: Algorithms and Applications, John Wiley & Sons, February 2000
16. T. Joachims, "Making large-scale SVM learning practical. Advances in kernel methods-support vector learning", B. Scoelkopf and C. Burges and A. Smola (ed.), MIT-Press, 1999