Vehicle recognition based on Gabor and Log-Gabor transforms

Abstract

Image-based vehicle recognition is usually addressed as a supervised classification problem. Here, vehicle recognition is performed using two different transforms such as Gabor and Log-Gabor. First the images are convolved with Gabor and LogGabor filter with different scales and orientations. Then mean and standard deviation are computed for all the filtered images. These features are fed to SVM classifier for further training and classification. The experimentation is carried out in GTI database. From the experiments it is revealed that the LogGabor transform significantly outperforms the standard Gabor transform for image-based vehicle recognition.

Human Face Detection Techniques: A Comprehensive Review and Future Research Directions

“…The presented model uses the intense texture characteristics gathered from phase information to detect facial expression. Priyadharshini et al [155] compared Gabor and Log Gabor in vehicle recognition and proved the superiority of Log Gabor in vehicle recognition. Yakun Zhang et al [156] presented a solution to the parameter adjustment of the Gabor filter with an application in finger vein detection.…”