A survey of decision fusion and feature fusion strategies for pattern classification

IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India)

Volumn 27, Issue 4, 2010, Pages 293-307

  Mangai, Utthara Gosa ^a   Samanta, Suranjana ^a   Das, Sukhendu ^a   Chowdhury, Pinaki Roy ^b  

^a INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

^b Ministry of Defence   (India)

Author keywords

Accuracy; Classifier selection; Combining classifiers; Decision fusion; Feature fusion; Feature ranking; Feature selection

Indexed keywords

CLASSIFIER SELECTION; DECISION FUSION; FEATURE FUSION; FEATURE RANKING; FEATURE SELECTION;

CLASSIFIERS; SURVEYS;

FEATURE EXTRACTION;

EID: 77954234443     PISSN: 02564602     EISSN: 09745971     Source Type: Journal    
DOI: 10.4103/0256-4602.64604     Document Type: Article

References (66)

1. B. V. Dasarathy, Decision Fusion, Computer Society Press, 1994.
2. L. I. Kuncheva, J. C. Bezdek, and R. P. W. Duin, "Decision templates for multiple classifier fusion: an experimental comparison," Pattern Recognition, vol.34, pp. 299- 314, February 2001.
3. T. K. Ho, J. J. Hull, and S. N. Srihari, "Decision in multiple classifier systems," IEEE Trans. Pattern Analysis and Machine Intelligence, vol.16, pp. 66-75, January 1994.
4. C. M. Bishop, "Neural Networks for Pattern Recognition", Oxford University Press, 1995.
5. B. V. Dasarathy, "Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques", IEEE Computer Society Press, 1995.
6. A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum Likelihood from Incomplete Data via the EM Algorithm," Journal of the Royal Statistical Society, vol.B 39, pp. 1-38, January 1977.
7. L. Xu, A. Krzyzak, and C. Y. Suen, "Methods of combining multiple classifiers and their applications to handwriting recognition," IEEE Trans. Systems, Man, and Cybernetics, vol.22, pp. 418-435, March 1992.
8. J. V. Kittler, M. Hatef, R. P. W. Duin, and J. Matas, "On combining classifiers," IEEE Trans. Pattern Analysis and Machine Intelligence, vol.20, pp. 226-239, March 1998.
9. L. Lam and C. Y. Suen, "Optimal combinations of pattern classifiers," Pattern Recog-nition Letters, vol.16, pp. 945-954, September 1995.
10. K. Woods, W. P. Kegelmeyer, and K. Bowyer, "Combination of multiple classifiers using local accuracy estimates," IEEE Trans. Pattern Analysis and Machine Intelligence, vol.19, pp. 405-410, April 1997.
11. L. I. Kuncheva and C. J. Whitaker, "Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy," Machine Learning, vol.51, pp. 181-207, May 2003.
12. M. Dash and H. Liu, "Feature selection for classification," Intelligent Data Analysis, vol.1, pp. 131-156, August 1997.
13. H. Liu and L. Yu, "Toward integrating feature selection algorithms for classification and clustering," IEEE Trans. Knowledge and Data Engineering, vol.17, pp. 491-502, April 2005.
14. S. Samanta and S. Das, "A Fast Supervised Method of Feature Ranking and Selection for Pattern classification," in Accepted in Third International Conference on Pattern Recognition and Machine Intelligence (PReMi'09), LNCS Publication, Delhi, Dec. 2009.
15. S. Samanta and S. Das, "Unsupervised Texture Segmentation using Feature Selection and Fusion," in Accepted in IEEE International Conference on Image Processing (ICIP'09), Cairo, Nov. 2009.
16. Q. S. Sun, S. G. Zeng, Y. Liu, P. A. Heng, and D. S. Xia, "A new method of feature fusion and its application in image recognition," Pattern Recognition, vol.38, pp. 2437- 2448, December 2005.
17. J. Yang, J. Y. Yang, D. Zhang, and J. Lu, "Feature fusion: parallel strategy vs. serial strategy," Pattern Recognition, vol.36, pp. 1369-1381, June 2003.
18. G. J. Briem, J. A. Benediktsson, and J. R. Sveinsson, "Multiple classifiers applied to multisource remote sensing data," IEEE Trans. Geoscience and Remote Sensing, vol.40, pp. 2291-2299, October 2002.
19. P. C. Smits, "Multiple classifier systems for supervised remote sensing image classification based on dynamic classifier selection," IEEE Trans. Geoscience and Remote Sensing, vol.40, pp. 801-823, April 2002.
20. V. D. Linden and B. S. Waske, "Classifying multilevel imagery from SAR and optical sensors by decision fusion," IEEE Trans. Geoscience and Remote Sensing, vol.46, pp. 1457-1466, May 2008.
21. S. Prasad and L. M. Bruce, "Decision fusion with confidence-based weight assignment for hyperspectral target recognition," IEEE Trans. Geoscience and Remote Sensing, vol.46, pp. 1448-1456, May 2008.
22. A. S. Constantinidis, M. C. Fairhurst, and A. F. R. Rahman, "A new multi-expert decision combination algorithm and its application to the detection of circumscribed masses in digital mammograms," Pattern Recognition, vol.34, pp. 1527-1537, August 2001.
23. R. R. Brooks, P. Ramanathan, and A. M. Sayeed, "Distributed target classification and tracking in sensor networks," Proceedings of the IEEE, vol.38, pp. 1163-1171, August 2003.
24. Q. Tao and R. Veldius, "Threshold-optimized decision-level fusion and its application to biometrics," Pattern Recognition, vol.19, pp. 823-836, May 2009.
25. N. E. Mitrakis, J. B. Thoecharis, and V. Petridis, "Amultilayered neuro-fuzzy classifier with self-organizing properties," Fuzzy Sets and Systems, vol.159, pp. 3132-3159, December 2008.
26. A. R. Mirhosseini, H. Y. Lam, and T. K. M. Pham, "Human face image recognition: An evidence aggregation approach," Computer Vision and Image Understanding, vol.23, pp. 213-230, August 1998.
27. M. A. Herraez, J. Domingo, and F. J. Ferri, "Combining similarity measures in content based image retrieval," Pattern Recognition Letters, vol.29, pp. 2174-2181, December 2008.
28. X. Chen, Y. Zhao, Y. Zhang, and R. Harrison, "Combining SVM classifiers using genetic fuzzy systems based on auc for gene expression data analysis," in International Symposium on Bioinformatics Research and Applications, Atlanta, May 2007, vol.4463, pp. 496-505.
29. C. L. Blake and C. J. Merz, "UCI repository of machine learning databases," http://archive.ics.uci.edu/ml/.
30. "VisTex Database," http://vismod.media.mit.edu/vismod/imagery/ VisionTexture/vistex .html.
31. T. Drugman, M. Gurban, and J. P. Thiran, "Relevant Feature Selection for Audio-Visual Speech Recognition," in IEEE 9th Workshop on Multimedia Signal Processing, Crete, Oct. 2007, pp. 179-182.
32. S. Manikandan and V. Rajamani, "A Mathematical Approach for Feature Selection and Image Retrieval of Ultra Sound Kidney Image Databases," European Journal of Scientific Research, vol.24, pp. 163-171, December 2008.
33. L. I. Kuncheva, "Combining Pattern Classifiers: Methods and Algorithms," Wiley Inter-science, 2004.
34. L. I. Kuncheva, "Switching between selection and fusion in combining classifiers: An experiment," IEEE Trans. Systems, Man and Cybernetics, vol.32, pp. 146-156, April 2002.
35. N. Littlestone and M. Warmth, "Weighted majority algorithm," Information and Computation, vol.108, pp. 212-261, February 1994.36
36. Y. S. Huang and C. Y. Suen, "A method of combining multiple experts for the recog-nition of unconstrained handwritten numerals," IEEE Trans. Pattern Analysis and Machine Intelligence, vol.17, pp. 90-94, January 1995.
37. P. D. Gader, M. A. Mohamed, and J. M. Keller, "Fusion of handwritten word classifiers," Pattern Recognition Letters, vol.17, pp. 577-584, May 1996.
38. G. Shafer, A Mathematical Theory of Evidence, Princeton University Press, 1976.
39. K. Fukunaga, "Introduction to Statistical Pattern Recognition, Second Edition (Computer Science and Scientific Computing Series)," Academic Press, 1990.
40. J. C. Schlimmer, "Efficiently inducing determinations: Acomplete and systematic search algorithm that uses optimal pruning," in International Conference on Machine Learning (Morgan Kaufmann Publisher), Amherst, Jun. 1993, pp. 284-290.
41. M. Kudo and J. Sklansky, "Comparison of algorithms that select features for pattern classifiers," Pattern Recognition, vol.33, pp. 25-41, January 2000.
42. H. Liu and R. Setiono, "Aprobabilistic approach to feature selection -a filter solution," in International Conference on Machine Learning (Morgan Kaufmann Publisher), Bari, Jun. 1996, pp. 319-327.
43. J. G. Dy and C. E. Brodley, "Feature subset selection and order identification for unsupervised learning," in International Conference on Machine Learning (Morgan Kaufmann Publisher), Stanford, Jun. 2000, pp. 247-254.
44. Y. Li, M. Dong, and J. Hua, "Localised feature selection for clustering," Pattern Recognition Letters, vol.29, pp. 10-18, January 2008.
45. A. Frank, D. Geiger, and Z. Yakhini, "Adistance-based branch and bound feature selection algorithm," in Conference on Uncertainty in AI, Mexico, Aug. 2003, pp. 241-248.
46. X. Guorong, C. Peiqi, and W. Minhui, "Bhattacharyya distance based feature selection," in International Conference on Pattern Recognition, Vienna, Aug. 1996, pp. 195-199.
47. J. Li, S. Chu, J. H. Chang, and J. Pan, "Discriminant feature fusion strategy for supervised learning," in International Conference on Intelligent Information Hiding and Multimedia Signal, California, Dec. 2006, pp. 301-304.
48. A. Patra and S. Das, "Dual space based face recognition using feature fusion," in International Conference on Visual Information Engineering, Bangalore, Sept. 2006, pp. 155-160.
49. O. A. Shiba, W. Saeed, M. N. Sulaiman, F. Ahmad, and A. Mamat, "Toward optimal feature subset selection," in IEEE Student Conference on Research and Development, Aug. 2003, pp. 376-380.
50. D. W. Liang, Q. M. Huang, S. Q. A. Jiang, H. X. Yao, and W. Gao, "Mean-shift blob tracking with adaptive feature selection and scale adaptation," in International Conference on Image Processing, San Antonio, Sept. 2007, pp. 369-372.
51. N. S. Madsen, C. Thomsen, and J. M. Pena, "Unsupervised feature subset selection," in Proc. Workshop on Probabilistic Graphical Models for Classification (PKDD'03), Croatia, Sept. 2003, pp. 71-82.
52. Y. Zhao, L. Zhang, and P. Li, "Texture feature fusion for high resolution satellite image classification," in International Conference on Computer Graphics, Imaging and Vision, Beijing, Jul. 2005, pp. 19-23.
53. K. Schneider, "A new feature selection score for multinomial Naive Bayes text clas-sification based on KL-divergence," in 42nd Annual Meeting of the Association for Computational Linguistics, Barcelona, Jul. 2004, pp. 186-189.
54. M. Dash, K. Choi, P. Scheuermann, and H. Liu, "Feature selection for clustering a filter solution," in International Conference on Data Mining, Maebashi city, Dec. 2002, pp. 115-122.
55. D. J. Slotta, J. P. Vergara, N. Ramakrishnan, and L. S. Heath, "Algorithms for feature selection in rank-order spaces," Tech. Rep., 2005.
56. Z. Zhao and H. Liu, "Searching for interacting features," in The 20th International Joint Conference on AI (IJCAI-07), Hyderabad, Jan. 2007, pp. 1156-1161
57. M. A. Hall, "Correlation-based feature selection for discrete and numeric class machine learning," in Proceedings 17th International Conference on Machine Learning, Stanford, Jun. 2000, pp. 359-366.
58. P. Mitra, C. A. Murthy, and S. K. Pal, "Unsupervised feature selection using feature similarity," IEEE Trans. Pattern Analysis and Machine Intelligence, vol.24, pp. 301- 312, March 2002.
59. B. Guo, R. I. Damper, S. R. Gunna, and J. D. B. Nelsona, "A fast separability-based feature-selection method for high-dimensional remotely sensed image classification," Pattern Recognition, vol.41, pp. 1653-1662, May 2008.
60. B. Cao, D. Shen, J. Sun, Q. Yang, and Z. Chen, "Feature selection in a kernel space," in International Conference on Machine Learning, Oregon, Jun. 2007, pp. 121-128.
61. J. Yang and J. Y. Yang, "Generalized K-L transform based combined feature extrac-tion," Pattern Recognition, vol.35, pp. 295-297, January 2002.
62. W. Li, W. Gong, Y. Liang, and W. Chen, "Feature selection based on KPCA, SVM and GSFS for face recognition," in International Conference on Advances in Pattern Recognition, Bath, Aug. 2005, pp. 344-350.
63. H. M. Genc, Z. Cataltepe, and T. Pearson, "A PCA/ICA based feature selection method and its application for corn fungi detection," in Eusipco (European Signal Processing Conference), Poland, Sep 2007, pp. 970-974.
64. B. Paskaleva, M. M. Hayat, Z. Wang, J. S. Tyo, and S. Krishna, "Canonical correlation feature selection for sensors with overlapping bands: Theory and application," IEEE Trans. on Geoscience and Remote Sensing, vol.46, pp. 3346-3358, October 2008.
65. Q. S. Sun, S. G. Zeng, P. A. Heng, and D. S. Xia, "Feature fusion method based on canonical correlation analysis and handwritten character recognition," in IEEE Conference on Control, Automation, Robotics and Vision Conference, Kunming, Dec. 2004, pp. 1547-1552
66. D. Puig and M. A. Garcia, "Automatic texture feature selection for image pixel classification," Pattern Recognition, vol.39, pp. 1996-2009, November 2006.