"Gabor filter"의 두 판 사이의 차이

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== 노트 ==
 
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* In image processing, a Gabor filter, named after Dennis Gabor, is a linear filter used for edge detection.<ref name="ref_74a2">[http://accord-framework.net/docs/html/T_Accord_Imaging_Filters_GaborFilter.htm GaborFilter Class]</ref>
 
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* In the spatial domain, a 2D Gabor filter is a Gaussian kernel function modulated by a sinusoidal plane wave.<ref name="ref_74a2" />
 
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* 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.<ref name="ref_c7dd">[https://stackoverflow.com/questions/21881971/filtering-using-gabor-filter Filtering using Gabor filter]</ref>
 
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* The first method integrates Gabor filters with labeling algorithm for edge detection and object segmentation.<ref name="ref_3718">[https://dl.acm.org/doi/10.1145/986537.986651 Efficient edge detection and object segmentation using Gabor filters]</ref>
 
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* Some of the filters learned during training of the first layer of a CNN resemble the Gabor filter.<ref name="ref_353d">[https://ir.lib.uwo.ca/etd/6155/ "Gabor Filter Initialization And Parameterization Strategies In Convolu" by Long Pham]</ref>
 
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* Gabor filters are extremely good at extracting features within an image.<ref name="ref_353d" />
 
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* Gabor filters are a traditional choice for obtaining localised frequency information.<ref name="ref_2129">[https://www.peterkovesi.com/matlabfns/PhaseCongruency/Docs/convexpl.html Log-Gabor Filters]</ref>
 
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* This difficulty can be seen if we look at the transfer function of an even-symmetric Gabor filter in the frequency domain.<ref name="ref_2129" />
 
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* Transfer function of a high bandwidth even-symmetric Gabor filter.<ref name="ref_2129" />
 
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* In this model, scene images are convolved by the multiscale and multiorientation Gabor filters.<ref name="ref_5b3d">[https://www.hindawi.com/journals/mpe/2015/109718/ A New Scene Classification Method Based on Local Gabor Features]</ref>
 
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* Given a scene image, we firstly convolve it with 2D Gabor filters.<ref name="ref_5b3d" />
 
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* This is an example of how to create Gabor filters in Fiji using Beanshell scripting.<ref name="ref_3275">[https://imagej.net/Gabor_Filter_script Gabor Filter script]</ref>
 
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* Demonstration of a Gabor filter applied to the Leaf sample image.<ref name="ref_3275" />
 
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* This script calculates a set of Gabor filters over the selected image.<ref name="ref_3275" />
 
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* A design patent image retrieval method based on Gabor filter and LBP is proposed in the paper.<ref name="ref_4989">[https://www.scientific.net/paper-keyword/gabor-filter Scientific.Net]</ref>
 
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* Multi-direction and multi-scale Gabor filters are employed to detect directions of road texture.<ref name="ref_4989" />
 
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* In this paper, we propose the combination of two visual features with the Gabor filters and LBP for music genre classification.<ref name="ref_4989" />
 
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* The algorithm is based on Laplacian pyramid and Gabor filters.<ref name="ref_4989" />
 
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* Texture features generated by Gabor filters have been increasingly considered and applied to image analysis.<ref name="ref_500d">[https://uwaterloo.ca/vision-image-processing-lab/publications/designing-gabor-filters-optimal-texture-separability Designing Gabor filters for optimal texture separability | Vision and Image Processing Lab]</ref>
 
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* In the paper, Gabor filter is considered as a Gabor atom detector.<ref name="ref_aaa7">[https://link.springer.com/chapter/10.1007/978-3-642-02611-9_7 An Analysis of Gabor Detection]</ref>
 
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* Constructs the Gabor filter with the specified parameters and performs convolution.<ref name="ref_b183">[https://dsp.stackexchange.com/questions/14714/understanding-the-gabor-filter-function Understanding the Gabor filter function]</ref>
 
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* The Log-Gabor filter is able to describe a signal in terms of the local frequency responses.<ref name="ref_6f5b">[https://en.wikipedia.org/wiki/Log_Gabor_filter Log Gabor filter]</ref>
 
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* Indeed, any application that uses Gabor filters, or other wavelet basis functions may benefit from the Log-Gabor filter.<ref name="ref_6f5b" />
 
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* Because of this, the Gabor filter is a good method for simultaneously localizing spatial/temporal and frequency information.<ref name="ref_6f5b" />
 
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* A Gabor filter in the space (or time) domain is formulated as a Gaussian envelope multiplied by a complex exponential.<ref name="ref_6f5b" />
 
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* Gabor filters are special classes of band pass filters, i.e., they allow a certain ‘band’ of frequencies and reject the others.<ref name="ref_e3f5">[https://medium.com/@anuj_shah/through-the-eyes-of-gabor-filter-17d1fdb3ac97 Through The Eyes of Gabor Filter]</ref>
 
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* A Gabor filter can be viewed as a sinusoidal signal of particular frequency and orientation, modulated by a Gaussian wave.<ref name="ref_e3f5" />
 
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* When a Gabor filter is applied to an image, it gives the highest response at edges and at points where texture changes.<ref name="ref_e3f5" />
 
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* Demonstration of a Gabor filter applied to Chinese OCR.<ref name="ref_594c">[https://en.wikipedia.org/wiki/Gabor_filter Gabor filter]</ref>
 
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* Gabor filters are directly related to Gabor wavelets, since they can be designed for a number of dilations and rotations.<ref name="ref_594c" />
 
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* Therefore, usually, a filter bank consisting of Gabor filters with various scales and rotations is created.<ref name="ref_594c" />
 
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* Gabor filters have also been widely used in pattern analysis applications.<ref name="ref_594c" />
 
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===소스===
 
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<references />
 
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== 메타데이터 ==
 
== 메타데이터 ==
  

2020년 12월 28일 (월) 07:17 판

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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.[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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