A commonly used representation of a visual pattern is the set of marginal probability distributions of the output of a bank of filters (Gaussian, Laplacian, Gabor etc...). This representation has been used effectively for a variety of vision tasks including texture classification, texture synthesis, object detection and image retrieval. This paper examines the ability of this representation to ...

This paper illustrates the use of Gabor wavelet transform on satellite images to classify the land in to crop land and noncrop land and to classify different crops. The input image is enhanced first using Colour Space Transform and Discrete Cosine Transform, and then a filter bank consisting of Gabor wavelets is used to extract texture features from the satellite image. The feature formation pr...

Objective(s): We evaluated edge artifacts in relation to phantom diameter and reconstruction parameters in point spread function (PSF)-based positron emission tomography (PET) image reconstruction.Methods: PET data were acquired from an original cone-shaped phantom filled with 18F solution (21.9 kBq/mL) for 10 min using a Biograph mCT scanner. The images were reconstructed using the baseline or...

We present results on the recognition accuracy of a continuous speech, speaker independent HMM recognition system that incorporates a novel noise reduction algorithm. The algorithm is a minimum mean square error estimation tailored for a filter-bank front-end. It introduces a significant improvement over similar published algorithms by incorporating a better statistical model for the filter-ban...

In this paper, we propose a new feature extraction method that combines both HMT-based denoising and weighted filter bank analysis for robust speech recognition. The proposed method is made up of two stages in cascade. The first stage is denoising process based on the wavelet domain Hidden Markov Tree model, and the second one is the filter bank analysis with weighting coefficients obtained fro...

in this paper, a novel matched filter based on a new kernel function with cauchy distribution is introduced to improve the accuracy ofthe automatic retinal vessel detection compared with other available matched filter‑based methods, most notably, the methods builton gaussian distribution function. several experiments are conducted to pick the best values of the parameters for the new designedfi...

in this paper, gaussian and elliptic high pass filters are analyzed for image sharpening qualitatively and quantatively . the filters are implemented in frequency domain using matlab software. experiments are performed to compare the performance of both the filters ,processed images are presented. the results demonstrate that elliptic yields better results.

The Mel Frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. In this paper to achieve a satisfactorily performance in Automatic Speech Recognition (ASR) applications we introduce a noise robust new set of MFCC vector estimated through following steps. First, spectral mean normalization is a pre-processing which applies to t...

In this paper, we study texture discrimination based on two filter families, Gabor and Hermite, which agree with the Gaussian derivative model of the human visual system. In the first part, discrimination of different textures, based on the output energy of these filters, is compared using the Fisher criterion and classification result. Results show that the presented filter bank is suitable fo...

In this paper, we propose a novel variational method for unsupervised texture segmentation. We use a Gabor filter bank to extract texture features. Some of the filtered channels form a multidimensional Gaborian feature space. To avoid deforming contours directly in a vector-valued space we use a Gaussian mixture model to describe the statistical distribution of this space and get the boundary a...