Title :
Object Recognition Using Log-Polar Wavelet Mapping
Author :
Matungka, Rittavee ; Zheng, Yuan F. ; Ewing, Robert L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Ohio State Univ., Columbus, OH
Abstract :
This paper proposes a rotation and scale invariant object recognition method which combines image feature extraction in Cartesian coordinate with the log-polar mapping and similarity measure techniques for classification. The method yields robustness for fast computation without any rescale needed in the target image. The method also does not use motion estimation. Thus, the method is also robust in recognizing objects without prior information of the objectpsilas motion or previous location. Experiments with real video sequences are provided to verify the effectiveness of the proposed approach in practice.
Keywords :
feature extraction; image classification; object recognition; wavelet transforms; Cartesian coordinate; image classification; image feature extraction; log-polar wavelet mapping; rotation invariant object recognition; scale invariant object recognition; similarity measure technique; Face; Feature extraction; Force measurement; Image coding; Image processing; Image registration; Military computing; Object recognition; Robustness; Video sequences; image feature extraction; log-polar; wavelet;
Conference_Titel :
Tools with Artificial Intelligence, 2008. ICTAI '08. 20th IEEE International Conference on
Conference_Location :
Dayton, OH
Print_ISBN :
978-0-7695-3440-4
DOI :
10.1109/ICTAI.2008.156