Gabor frames, especially digital Gabor filters, have long been known as indispensable tools for local time-frequency analysis of discrete signals. With strong orientation selectivity, tensor products discrete (tight) Gabor frames also see their applications in image analysis and restoration. However, the lack of multi-scale structures existing in MRA-based wavelet (tight) frames makes discrete ...

Orthogonal and biorthogonal wavelets became very popular image processing tools but exhibit major drawbacks, namely a poor resolution in orientation and the lack of translation invariance due to aliasing between subbands. We propose here the construction of log-Gabor wavelet transforms which allow exact reconstruction and strengthen the excellent mathematical properties of the Gabor filters. Tw...

This work revolves around Gabor filters. It involves theoretical aspects such as the uncertainty principle as well as practical issues such as filter bank design and application of Gabor filters to texture segmentation. This thesis is composed of three main parts. In the first part, we explore the role of the metric of the Gabor feature space, and its usefulness in capturing what we refer to as...

Gabor schemes of multiscale image representation are useful in many computer vision applications. However, the classic Gabor expansion is computationally expensive due to the lack of orthogonality of Gabor functions. Some alternative schemes, based on the application of a bank of Gabor filters, have important advantages such as computational efficiency and robustness, at the cost of redundancy ...

Gabor-based face representation has achieved enormous success in face recognition. This research addresses a hybrid neural network solution for face recognition trained with Gabor features. The system is commenced on convolving a face image with a series of Gabor filter coefficients at different scales and orientations. The neural network employed for face recognition is based on BAM for dimens...

We present a method that analyzes a two-dimensional magnitude spectrogram S(f, t) into its local constituent spectro-temporal amplitudes A(f, t), frequencies F (f, t), orientations Θ(f, t), and phases φ(f, t). The method operates by performing a twodimensional local Gabor-like analysis of the spectrogram, retaining only the parameters of the 2D-Gabor filter with maximal amplitude response withi...

We introduce visual object detection architecture, making full use of technical merits of so-called multi-scale feature correspondence in the neurally inspired Gabor pyramid. The remarkable property of the multi-scale Gabor feature correspondence is found with scale-space approaches, which an original image Gabor-filtered with the individual frequency levels is approximated to the corresponding...