Two Functions for Texture Feature Extraction Using Gabor Filter Method

Resource Overview

Two Gabor filter functions for texture feature extraction, implementing 5 scales and 6 orientations, applied to grayscale images with code implementation details

Detailed Documentation

In this documentation, we present the Gabor filter method for texture feature extraction. This approach utilizes two core functions that compute filter responses across 5 different scales and 6 distinct orientations, specifically designed for grayscale image processing. The implementation typically involves creating a bank of Gabor filters through mathematical functions that generate complex sinusoidal plane waves modulated by Gaussian envelopes. Each filter in the bank corresponds to a specific scale (wavelength) and orientation combination, allowing comprehensive texture analysis. Through this methodology, we can effectively capture detailed texture information and spatial frequency characteristics within images, enabling better understanding of image features and content. The code implementation generally includes parameters for filter bandwidth, aspect ratio, and phase offset, with convolution operations applied to extract multi-scale texture responses.