Gabor Filter
Use Gabor filters for texture analysis, orientation response, and feature extraction with live kernel and output previews.
The Gabor filter is a linear filter used for texture analysis and edge detection at specific orientations and frequencies. Tune the parameters and compare the kernel visualization with the filtered output; preview timing varies by browser, device, and image size.
How to Use Gabor Filter
- Upload an image: Upload one of the formats listed by the tool (JPG, PNG, WebP) and wait for the local preview.
- Adjust settings and process: Adjust the Gabor filter parameters, kernel size, sigma, theta, lambda, gamma, and psi, to analyze texture patterns.
- Review and download: Review the result, then download it in one of the formats offered by this tool.
Frequently asked questions
What is a Gabor filter?
A Gabor filter is a sinusoidal wave modulated by a Gaussian envelope. It responds strongly to textures at a specific orientation (theta) and frequency (1/lambda), making it ideal for feature extraction, texture classification, and edge detection.
What do the parameters mean?
Sigma controls the Gaussian spread, theta sets the orientation, lambda is the sinusoidal wavelength, gamma adjusts the aspect ratio (elongation), and psi is the phase offset of the wave.
How do I choose the right Gabor filter parameters?
Start with frequency matching your texture scale (sigma 3-5 for fine, 7-10 for coarse textures). Set theta to the dominant orientation. Lambda controls wavelength: smaller values detect finer patterns. Use multiple orientations (0°, 45°, 90°, 135°) for orientation-independent texture analysis.
Is the Gabor Filter tool free?
Yes. All tools on Pixlane are free with no signup required.
Does it reuse cached assets on repeat visits?
Browser caching can speed repeat visits; uncached site assets can still require an internet connection.
What image formats are supported?
JPG, PNG, and WebP are supported.
What is the Gabor kernel visualization?
The kernel preview shows the 2D sinusoidal wave modulated by the Gaussian envelope. Bright and dark bands indicate the positive and negative lobes of the filter. This helps you verify orientation, frequency, and aspect ratio before applying to images.
What are common applications of Gabor filters in computer vision?
Gabor filters are used for texture classification, fingerprint enhancement, iris recognition, document analysis, and defect detection. A bank of Gabor filters at multiple orientations and scales forms a powerful texture descriptor.