for Efficient Object Recognition
Mi Young Nam, Phill Kyu Rhee · 2005
This paper describes, using situational awareness and Genetic algo- rithm, a run-time optimization methodology of the Gabor wavelet parameters so that it produces a feature space for efficient object recognition. Gabor wave- let efficiently extracts the feature space of orientation selectivity, spatial fre- quency and spatial localization. Most previous object recognition approaches using Gabor wavelet do not include systematic optimization of the parameters for the Gabor kernel, even though the system performance might be much sen- sitive to the characteristics of the Gabor parameters. This paper explores effi- cient object recognition using adaptive Gabor wavelet based situational aware method. The superiority of the proposed system is shown using IT-Lab, FERET and Yale face database. We achieved encouraging experimental results.