introduction: the process of discriminating among benign and malignant hyperplasia begun with subjective methods using light microscopy and is now being continued with computerized morphometrical analysis requiring some features. one of the main features called volume percentage of stroma (vps) is obtained by calculating the percentage of stroma texture. currently, this feature is calculated by...

Multi-view face detection in open environments is a challenging task, due to the wide variations in illumination, face appearances and occlusion. In this paper, a robust method for multi-view face detection in open environments, using a combination of Gabor features and neural networks, is presented. Firstly, the effect of changing the Gabor filter parameters (orientation, frequency, standard d...

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: The process of discriminating among benign and malignant hyperplasia begun with subjective methods using light microscopy and is now being continued with computerized morphometrical analysis requiring some features. One of the main features called Volume Percentage of Stroma (VPS) is obtained by calculating the percentage of stroma texture. Currently, this feature is calculated ...

An elementary function that is now commonly referred to Gabor function, Gabor filter and Gabor wavelet was derived from uncertainty relation for information by Gabor to overcome the representation limit of Fourier analysis. Analyzing a signal by a Gabor filter in terms of convolution or spatial filtering, two pieces of information—phase and magnitude—can be obtained. In the paper, Gabor filter ...

Gabor filter-based features have been successfully used for pattern recognition. When using Gabor features, one needs to optimize Gabor filter parameters because the performance of a pattern recognition system with Gabor features depends strongly on the parameter values of the Gabor filter. In this paper, we discuss a method of optimizing Gabor filter parameters for pattern recognition. In expe...

This paper describes a new method for the automated segmentation and extraction of cardiac MRI tagging lines. Our method is based on the novel use of a 2D Gabor filter bank. By convolving the tagged input image with our Gabor filters, the tagging lines are automatically enhanced and segmented out. We design the Gabor filter bank based on the input image’s spatial and frequency characteristics. ...

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...

This paper addresses new face recognition method based on Independent Component Analysis(1CA) and Gabor filter. Our method consists of three parts. The first part is Gabor filtering on predefined fiducial points that could represent robust facial features from original face image. The second part is transforming the facial features into the basis space of ICA, which is able to represent individ...

We propose a novel human face recognition approach in this paper, based on two-dimensional Gabor filtering and supervised classification. The feature extraction technique proposed in this article uses 2D Gabor filter banks and produces robust 3D face feature vectors. A supervised classifier, using minimum average distances, is developed for these vectors. The recognition process is completed by...