A [[Gabor filter]] is directly related to the [[Gabor function]]. **Gabor Function:** The Gabor function is a complex mathematical function that combines a Gaussian envelope with a sinusoidal wave. It has parameters that control its shape, orientation, and frequency. It's named after [[Dennis Gabor]], who introduced it in 1946. **Gabor Filter:** A Gabor filter is a linear filter (an image processing tool) that uses the Gabor function as its kernel. This means it convolves the Gabor function with an input image to produce an output image. The filter is particularly effective at extracting specific frequencies and orientations from the image, making it useful for various tasks. **Key applications and properties:** - **Edge detection:** Gabor filters are excellent at detecting edges in images because they can be tuned to specific orientations and frequencies, highlighting the boundaries between different regions. - **Texture analysis:** The filter can be used to analyze and characterize textures in images by capturing their dominant orientations and frequencies. - **Feature extraction:** Gabor filters are employed in machine learning and computer vision to extract meaningful features from images for tasks like object recognition and classification. - **Biological relevance:** The Gabor function has been found to resemble the receptive field profiles of simple cells in the visual cortex of some mammals, suggesting its potential significance in understanding biological vision. **Relationship between the two:** In essence, a Gabor filter is a practical implementation of the Gabor function. The mathematical properties of the Gabor function make it ideal for capturing specific image features, and the Gabor filter leverages these properties to perform useful image processing tasks. # References ```dataview Table title as Title, authors as Authors where contains(subject, "Gabor filter") sort title, authors, modified, desc ```