Title :
2D occluded object recognition using wavelets
Author :
Du, Tiehua ; Lim, Kah Bin ; Hong, Geok Soon ; Yu, Wei Miao ; Zheng, Hao
Author_Institution :
National Univ. of Singapore, Singapore
Abstract :
A 2D object recognition algorithm applicable for partial occluded object recognition is proposed. The boundary of object of interest is extracted first. Then we segment the boundary into curve segments using dominant points, followed by a proportional extension. Normalization is then performed for each segment to make them translation, orientation and scaling invariant. After that, each segment is represented by its wavelet descriptors at multi-scale. A hierarchical iterative matching is performed to identify the object from low to high resolution. Experiment result shows proposed recognition algorithm is robust to similarity transform, noise and occlusion, and it is computational efficient.
Keywords :
edge detection; feature extraction; hidden feature removal; image representation; image segmentation; object recognition; wavelet transforms; 2D occluded object recognition; boundary segmentation; curve segments; hierarchical iterative matching; image orientation; image scaling; image translation; noise; normalization; object boundary extraction; occlusion; partial occluded object recognition; segment representation; similarity transform; wavelet descriptors; wavelets; Computational efficiency; Feature extraction; Image segmentation; Iterative algorithms; Multi-stage noise shaping; Noise robustness; Object recognition; Pattern matching; Pattern recognition; Shape;
Conference_Titel :
Computer and Information Technology, 2004. CIT '04. The Fourth International Conference on
Print_ISBN :
0-7695-2216-5
DOI :
10.1109/CIT.2004.1357201