Gabor filter

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  1. The Gabor filter, named after Dennis Gabor, is a linear filter used in myriad of image processing application for edge detection, texture analysis, feature extraction, etc.[1]
  2. Gabor filters are special classes of band pass filters, i.e., they allow a certain ‘band’ of frequencies and reject the others.[1]
  3. A Gabor filter can be viewed as a sinusoidal signal of particular frequency and orientation, modulated by a Gaussian wave.[1]
  4. When the input image is convolved with all the Gabor filters the patterns are easily highlighted as shown in figure 3.[1]
  5. The Log-Gabor filter is able to describe a signal in terms of the local frequency responses.[2]
  6. Indeed, any application that uses Gabor filters, or other wavelet basis functions may benefit from the Log-Gabor filter.[2]
  7. Features formed from the response of Log-Gabor filters may form a good set of features for some applications because it can locally represent frequency information.[2]
  8. Because of this, the Gabor filter is a good method for simultaneously localizing spatial/temporal and frequency information.[2]
  9. A gabor filter set with a given direction gives a strong response for locations of the target images that have structures in this given direction.[3]
  10. Constructs the Gabor filter with the specified parameters and performs convolution.[4]
  11. The following images show the original Lenna picture and Gabor filter results for different sampling factors.[5]
  12. Demonstration of a Gabor filter applied to Chinese OCR.[6]
  13. Gabor filters are directly related to Gabor wavelets, since they can be designed for a number of dilations and rotations.[6]
  14. Therefore, usually, a filter bank consisting of Gabor filters with various scales and rotations is created.[6]
  15. Gabor filters have also been widely used in pattern analysis applications.[6]
  16. This is an example of how to create Gabor filters in Fiji using Beanshell scripting.[7]
  17. Demonstration of a Gabor filter applied to the Leaf sample image.[7]
  18. This script calculates a set of Gabor filters over the selected image.[7]
  19. A raster or matrix to be filtered lamda Wavelength of the cosine part of Gabor filter kernel in pixel.[8]
  20. This is the wavelength of the cosine factor of the Gabor filter kernel and herewith the preferred wavelength of this filter.[9]
  21. The images (of size 100 x 100) on the left show Gabor filter kernels with values of the wavelength parameter of 5, 10 and 15, from left to right, respectively.[9]
  22. The images (of size 100 x 100) on the left show Gabor filter kernels with values of the orientation parameter of 0, 45 and 90, from left to right, respectively.[9]
  23. The images (of size 100 x 100) on the left show Gabor filter kernels with values of the phase offset parameter of 0, 180, -90 and 90 dgerees, from left to right, respectively.[9]
  24. Analyzing a signal by a Gabor filter in terms of convolution or spatial filtering, two pieces of information—phase and magnitude—can be obtained.[10]
  25. In the paper, Gabor filter is considered as a Gabor atom detector.[10]
  26. In this example, we will see how to classify textures based on Gabor filter banks.[11]
  27. The images are filtered using the real parts of various different Gabor filter kernels.[11]
  28. Purpose: We propose a method and approach for cup and disc detection based on 2-D Gabor filter with the addition of some constraints.[12]
  29. The 2D-Gabor filters occupy an irreducible volume in a four-dimensional hyper-space of information whose axes can be interpreted as 2D visual space, Orientation and spatial frequency.[12]
  30. A novel peripheral processing method is proposed to segment total field strain distributions from interferometric deformation patterns by use of Gabor filters.[12]
  31. This novel strategy is specifically proposed for strain measurement with a Gabor filter used as a set of wavelets.[12]
  32. Gabor filters are a traditional choice for obtaining localised frequency information.[13]
  33. This difficulty can be seen if we look at the transfer function of an even-symmetric Gabor filter in the frequency domain.[13]
  34. Transfer function of a high bandwidth even-symmetric Gabor filter.[13]
  35. In image processing, a Gabor filter, named after Dennis Gabor, is a linear filter used for edge detection.[14]
  36. In the spatial domain, a 2D Gabor filter is a Gaussian kernel function modulated by a sinusoidal plane wave.[14]
  37. Some of the filters learned during training of the first layer of a CNN resemble the Gabor filter.[15]
  38. Gabor filters are extremely good at extracting features within an image.[15]
  39. We have taken this as an incentive by replacing the first layer of a CNN with the Gabor filter to increase speed and accuracy for classifying images.[15]
  40. We created two simple 5-layer AlexNet-like CNNs comparing grid-search to random-search for initializing the Gabor filter bank.[15]

소스

  1. ↑ 1.0 1.1 1.2 1.3 Through The Eyes of Gabor Filter
  2. ↑ 2.0 2.1 2.2 2.3 Log Gabor filter
  3. ↑ What is the Gabor filter? And what are its main uses?
  4. ↑ Understanding the Gabor filter function
  5. ↑ Active Stereo Vision
  6. ↑ 6.0 6.1 6.2 6.3 Gabor filter
  7. ↑ 7.0 7.1 7.2 Gabor Filter script
  8. ↑ gabor.filter function
  9. ↑ 9.0 9.1 9.2 9.3 Gabor filter for image processing and computer vision
  10. ↑ 10.0 10.1 An Analysis of Gabor Detection
  11. ↑ 11.0 11.1 Gabor filter banks for texture classification — skimage v0.19.0.dev0 docs
  12. ↑ 12.0 12.1 12.2 12.3 Applying a Set of Gabor Filter to 2D-Retinal Fundus Image to Det
  13. ↑ 13.0 13.1 13.2 Log-Gabor Filters
  14. ↑ 14.0 14.1 GaborFilter Class
  15. ↑ 15.0 15.1 15.2 15.3 "Gabor Filter Initialization And Parameterization Strategies In Convolu" by Long Pham

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