Gabor filter

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• In image processing, a Gabor filter, named after Dennis Gabor, is a linear filter used for edge detection.
• In the spatial domain, a 2D Gabor filter is a Gaussian kernel function modulated by a sinusoidal plane wave.
• I have implemented a Gabor filter but don't know how to convolve it with the input image so as to get the desired result.
• The first method integrates Gabor filters with labeling algorithm for edge detection and object segmentation.
• Some of the filters learned during training of the first layer of a CNN resemble the Gabor filter.
• Gabor filters are extremely good at extracting features within an image.
• Gabor filters are a traditional choice for obtaining localised frequency information.
• This difficulty can be seen if we look at the transfer function of an even-symmetric Gabor filter in the frequency domain.
• Transfer function of a high bandwidth even-symmetric Gabor filter.
• In this model, scene images are convolved by the multiscale and multiorientation Gabor filters.
• Given a scene image, we firstly convolve it with 2D Gabor filters.
• This is an example of how to create Gabor filters in Fiji using Beanshell scripting.
• Demonstration of a Gabor filter applied to the Leaf sample image.
• This script calculates a set of Gabor filters over the selected image.
• A design patent image retrieval method based on Gabor filter and LBP is proposed in the paper.
• Multi-direction and multi-scale Gabor filters are employed to detect directions of road texture.
• In this paper, we propose the combination of two visual features with the Gabor filters and LBP for music genre classification.
• The algorithm is based on Laplacian pyramid and Gabor filters.
• Texture features generated by Gabor filters have been increasingly considered and applied to image analysis.
• In the paper, Gabor filter is considered as a Gabor atom detector.
• Constructs the Gabor filter with the specified parameters and performs convolution.
• The Log-Gabor filter is able to describe a signal in terms of the local frequency responses.
• Indeed, any application that uses Gabor filters, or other wavelet basis functions may benefit from the Log-Gabor filter.
• Because of this, the Gabor filter is a good method for simultaneously localizing spatial/temporal and frequency information.
• A Gabor filter in the space (or time) domain is formulated as a Gaussian envelope multiplied by a complex exponential.
• Gabor filters are special classes of band pass filters, i.e., they allow a certain ‘band’ of frequencies and reject the others.
• A Gabor filter can be viewed as a sinusoidal signal of particular frequency and orientation, modulated by a Gaussian wave.
• When a Gabor filter is applied to an image, it gives the highest response at edges and at points where texture changes.
• Demonstration of a Gabor filter applied to Chinese OCR.
• Gabor filters are directly related to Gabor wavelets, since they can be designed for a number of dilations and rotations.
• Therefore, usually, a filter bank consisting of Gabor filters with various scales and rotations is created.
• Gabor filters have also been widely used in pattern analysis applications.

메타데이터

위키데이터

• ID : Q2447890

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말뭉치

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.
2. Gabor filters are special classes of band pass filters, i.e., they allow a certain ‘band’ of frequencies and reject the others.
3. A Gabor filter can be viewed as a sinusoidal signal of particular frequency and orientation, modulated by a Gaussian wave.
4. When the input image is convolved with all the Gabor filters the patterns are easily highlighted as shown in figure 3.
5. The Log-Gabor filter is able to describe a signal in terms of the local frequency responses.
6. Indeed, any application that uses Gabor filters, or other wavelet basis functions may benefit from the Log-Gabor filter.
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.
8. Because of this, the Gabor filter is a good method for simultaneously localizing spatial/temporal and frequency information.
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.
10. Constructs the Gabor filter with the specified parameters and performs convolution.
11. The following images show the original Lenna picture and Gabor filter results for different sampling factors.
12. Demonstration of a Gabor filter applied to Chinese OCR.
13. Gabor filters are directly related to Gabor wavelets, since they can be designed for a number of dilations and rotations.
14. Therefore, usually, a filter bank consisting of Gabor filters with various scales and rotations is created.
15. Gabor filters have also been widely used in pattern analysis applications.
16. This is an example of how to create Gabor filters in Fiji using Beanshell scripting.
17. Demonstration of a Gabor filter applied to the Leaf sample image.
18. This script calculates a set of Gabor filters over the selected image.
19. A raster or matrix to be filtered lamda Wavelength of the cosine part of Gabor filter kernel in pixel.
20. This is the wavelength of the cosine factor of the Gabor filter kernel and herewith the preferred wavelength of this filter.
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.
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.
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.
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.
25. In the paper, Gabor filter is considered as a Gabor atom detector.
26. In this example, we will see how to classify textures based on Gabor filter banks.
27. The images are filtered using the real parts of various different Gabor filter kernels.
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.
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.
30. A novel peripheral processing method is proposed to segment total field strain distributions from interferometric deformation patterns by use of Gabor filters.
31. This novel strategy is specifically proposed for strain measurement with a Gabor filter used as a set of wavelets.
32. Gabor filters are a traditional choice for obtaining localised frequency information.
33. This difficulty can be seen if we look at the transfer function of an even-symmetric Gabor filter in the frequency domain.
34. Transfer function of a high bandwidth even-symmetric Gabor filter.
35. In image processing, a Gabor filter, named after Dennis Gabor, is a linear filter used for edge detection.
36. In the spatial domain, a 2D Gabor filter is a Gaussian kernel function modulated by a sinusoidal plane wave.
37. Some of the filters learned during training of the first layer of a CNN resemble the Gabor filter.
38. Gabor filters are extremely good at extracting features within an image.
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.
40. We created two simple 5-layer AlexNet-like CNNs comparing grid-search to random-search for initializing the Gabor filter bank.