The paper presents texture classification using multichannel filters: Gabor filters and discrete wavelet transform. We have used a bank of 8 Gabor filters 2 wavelet filters: Daubeschies and Haar, for analyzing and classifying the textures in SAR images. The parameters of the Gabor filter bank are obtained using the energy measure of the response to the filters. The Fuzzy C-means classifier has ...

in this paper, a new method is presented for the detection of defects in random textures. in the training stage, the feature vectors of the normal textures’ images are extracted by using the optimal response of gabor wavelet filters, and their probability density is estimated by means of the gaussian mixture model (gmm). in the testing stage, similar to the previous stage,at  first, the feature...

This paper presents an unsupervised method of texture classification by combining the two most commonly used multi-resolution, multi-channel filters: Gabor filters and wavelet transform. We used a set of 8 Gabor filters and 2 wavelet filters: Daubeschies and Haar, for our analysis. The parameters (viz. frequency, orientation and size) of the Gabor filter bank are obtained by trial and error met...

In practice Gabor wavelet is often applied to extract relevant features from a facial image. This wavelet is constructed using filters of multiple scales and orientations. Based on Gabor’s theory of communication, two methods are proposed to acquire initial features from 2D images that are Gabor wavelet and Log-Gabor wavelet. Theoretically the main difference between these two wavelets is Log-G...

Digital Gabor filters are indispensable tools of local time-frequency analysis in signal processing. With strong orientation selectivity, discrete (tight) Gabor frames generated by 2D Gabor filters also see their wide applications in image processing and volume data processing. However, owing to the lack of multi-scale structures, discrete Gabor frames are less effective than multiresolution an...

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 ...

In this paper we first introduce the Gabor Wavelet Network (GWN) as a model-based approach for effective and efficient object representation. GWNs combine the advantages of the continuous wavelet transform with RBF networks. They have additional advantages such as invariance to some degree with respect to affine deformations. The use of Gabor filters enables the coding of geometrical and textur...

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...

In this article we want to introduce first the Gabor wavelet network as a model based approach for an effective and efficient object representation. The Gabor wavelet network has several advantages such as invariance to some degree with respect to translation, rotation and dilation. Furthermore, the use of Gabor filters ensured that geometrical and textural object features are encoded. The feas...

Introduction: A major problem facing the patients with chronic liver diseases is the diagnostic procedure.  The conventional diagnostic method depends mainly on needle biopsy which is an invasive method. There  are  some  approaches  to  develop  a  reliable  noninvasive  method  of  evaluating  histological  changes  in  sonograms. The main characteristic used to distinguish between the normal...