Gabor Wavelet Filter for Texture Extraction

Texture extraction using Gabor wavelet filters. The Gabor wavelet filter is a widely used filter in image processing that effectively extracts texture information from images. By applying Gabor wavelet filters with specific frequency and orientation parameters, we can obtain more detailed and accurate texture features, which are crucial for various computer vision tasks. In implementation, Gabor filters are typically created using complex sinusoidal plane waves modulated by Gaussian envelopes, with key parameters including wavelength (λ), orientation (θ), phase offset (φ), and aspect ratio (γ). Common code implementations involve generating Gabor kernels through mathematical functions like cv2.getGaborKernel() in OpenCV or custom MATLAB functions, followed by convolution operations with input images. Multiple filter responses at different orientations and scales are often combined to create comprehensive texture representations. Therefore, using Gabor wavelet filters for texture extraction represents a standard and effective approach in computer vision applications.