Evaluation of Image Edges using Gabor Filter
/ November 27, 2017

In the field of image processing, filters play an extremely important role. All image processing operations can be viewed as applying a series of filters to an image and transforming it in some way. Gabor filter is a particular type of filter, and it happens to be an important one. Gabor filter responses are widely and successfully used as general purpose features in many computer vision tasks, such as in texture segmentation, face detection and recognition, and iris recognition. In a typical feature construction the Gabor filters are utilized via multi-resolution structure, consisting of filters tuned to several different frequencies and orientations. The multi-resolution structure relates the Gabor features to wavelets, but the main difference, non-orthogonality, also is connected to the main weakness of the Gabor features: computational heaviness. The computational complexity prevents their use in many real-time or near real-time tasks, such as in object tracking. Gabor Filter Significance Gabor filters are orientation-sensitive filters, used for edge and texture analysis. It is named after Dennis Gabor. Certain specific bands of frequency components can be extracted by adjusting the orientation and center frequencies of the Gabor filter. They have enjoyed much attention in the field of 2D face recognition and…

Insert math as
$${}$$