Polynomial modulated filters with compact support and their application in image classification

Gabor filters are Gaussian modulated wavelets that due to their ability to extract features in different directions and frequencies in an image are used widely in different applications. However، because of their infinite support، an exact realization is not practically possible and an approximated realization results in losing performance. In this paper، a new modulated wavelet with compact support and close to Gabor wavelet is proposed. Due to its compact support، an exact and fast implementation is possible. To evaluate the performance of the proposed filters a comparative study between them and Gabor filters in two classification application containing semantic image classification and Farsi font recognition is given. The obtained results confirm the performance improvement of the proposed filters in both speed and precision.