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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 9    
Website: http://www.ijser.org
scirp IJSER >> Volume 3,Issue 9,September 2012
Novel Feature Fusion Method of Object Recognition Using Wavelet Transform
Full Text(PDF, )  PP.150‐159  
Author(s)
V.Subbaroyan, Dr.Selvakumar Raja
KEYWORDS
Colour moments, Object recognition, Gradient, Histogram, KNN Classifier, Texture, Wavelet transform
ABSTRACT
In this paper we propose a novel approach to recognize multiple view objects, considering features from frequency as well as spatial domains. A colour descriptor based on HSV histogram is used to obtain the spatial features using the colour moments. The frequency features are obtained using Discrete Wavelet Transform (DWT). The two features are then combined to get a feature set that describes the object more accurately. The extracted features are used as an input to the K Nearest Neighbor (K-NN) for classification. The evaluation of the system is carried on using COIL database and the performance of the proposed system is studied by varying the training set sizes. The study also includes the effect of noise and occlusion. Experimental results show that the proposed method of object identification is more accurate. 
References
[1] Bicchi A. and Kumar V., ―Robotic grasping and contact: A review,‖ in Proceedings of the IEEE International Conference on Robotics and Automation, ICRA’00, 2000, pp. 348–353.

[2] Nelson R. and Selinger A., ―A cubist approach to object recognition,‖ in ICCV’98, 1998, pp.614–621.

[3] Bjorkman M. and Kragic D., ―Combination of foveal and peripheral vision for object recognition and pose estimation,‖ Proceedings. IEEE International Conference on Robotics and Automation, ICRA’04, vol. 5, pp. 5135 – 5140, 2004.

[4] Kaiser M. and Dillman R., ―Building elementary robot skills from human demonstration,‖ Proceedings of the IEEE International Conference on Robotics and Automation, v. 3, pp. 2700– 2705, 1996.

[5] Chen J. and Zelinsky A., ―Programming by demonstration: removing suboptimal actions in a partially known configuration space,‖ Proceedings of the IEEE Intl. Conf. on Robotics and Automation (ICRA ’01), vol. 4, pp. 4096–4103, 2001.

[6] Ekvall S. and Kragic D., ―Interactive grasp learning based on human demonstration,‖ in Proc. IEEE/RSJ International Conference on Robotics and automation, ICRA’04, 2004.

[7] Petersson L., Jensfelt P., Tell D., Strandberg M., Kragic D., and Christensen H. I., ―Systems integration for real-world manipulation tasks,‖in IEEE International Conference on Robotics and Automation, ICRA 2002, vol. 3, 2002, pp. 2500 – 2505.

[8] Chaumette F., ―Image moments: a general and useful set of features for visual servoing,‖ IEEE Trans. on Robotics, vol. 20 (4), 2004.

[9] Taylor G. and Kleeman L., ―Grasping unknown objects with a humanoid robot,‖ Australiasian Conference on Robotics and Automation, 2002.

[10] Ekvall F. H. S. and Kragic D., ―Object recognition and pose estimation for robotic manipulation using color co-occurrence histograms,‖ in Proc. IEEE/RSJ International Conference Intelligent Robots and Systems, IROS’ 03, 2003.

[11] Selinger A. and Nelson R, ―A perceptual grouping hierarchy for appearance - based 3d object recognition,‖ CVIU, vol. 76, no. 1, pp. 83– 92, October 1999.

[12] Derrode and F. Ghorbel (2001), ―Robust and efficient Fourier-Mellin transform approximations for invariant grey-level image description and reconstruction‖, In Computer Vision and Image Understanding, 83(1):57-78

[13] Arbter K., Snyder W. E., Burkhardt H., and Hirzinger G., ―Application of affine-invariant Fourier descriptors to recognition of 3-d objects.‖ IEEE Trans. Pattern Anal. Mach. Intell., vol.12, no. 7, pp. 640–647, 1990.

[14] Singh R. and Papanikolopoulos N., ―Planar shape recognition by shape morphing.‖ Pattern Recognition, vol. 33, no. 10, pp. 1683–1699, 2000.

[15] Gdalyahu Y. and Weinshall D., ―Flexible syntactic matching of curves and its application to automatic hierarchical classification of silhouettes.‖ IEEE Trans. Pattern Anal. Mach. Intell., vol. 21, no. 12, pp. 1312–1328, 1999.

[16] Christopoulos Vassilios N. and Schrater Paul,‖ Handling shape and contact location uncertainty in grasping twodimensional planar objects‖ Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA, Oct 29 - Nov 2, 2007.

[17] M.K. Hu (1962), ―Visual pattern recognition by moment invariants‖, In Proc. IEEE Transactions on Information Theory, 8:179- 187

[18] A. Khotanzad and Y. Hua Hong (1990), ―Invariant image recognition by Zernike moments‖, In Proc. IEEE Transaction on Pattern Analysis and Machine Intelligence, 12(5):489-497.

[19] D. Lowe (2004), ―Distinctive image features from scaleinvariant key-points‖, In International Journal for Computer Vision, 60(2):91-110

[20] J. Friedman (1996), ―Another approach to polychotomous classification‖, Technical report, Department of Statistics, Stanford University

[21] J. Friedman (2010), ―A fast and Robust descriptor for multiple views object recognition‖, International Conference on Control, Automation, Robotics and Vision, ICARVC, 2010, Singapore, pp2166 - 2171

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