Object Recognition Based on Dual Tree Complex Wavelet Transform

S. Elakkiya, Audithan Sivaraman · Research Journal of Applied Sciences Engineering and Technology · 2014

Automated recognition of objects from images plays an important role in many computer vision systems such as robot navigation, object manipulation and content based image retrieval. In this study, an approach for object recognition based on Dual Tree Complex Wavelet Transform (DTCWT) is proposed. The proposed approach attempts to extract the detailed information of objects from the multi scale representation by DTCWT. The proposed system is tested on Columbia Object Image Library (COIL-100). All the objects are considered for the classification based on nearest neighbor classifier. The results show that the maximum recognition accuracy achieved by the proposed approach is 97.03%.

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