Gabor filter

수학노트
Pythagoras0 (토론 | 기여)님의 2020년 12월 28일 (월) 08:20 판 (→‎메타데이터)
(차이) ← 이전 판 | 최신판 (차이) | 다음 판 → (차이)
둘러보기로 가기 검색하러 가기

노트

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

메타데이터

위키데이터

Spacy 패턴 목록

  • [{'LOWER': 'gabor'}, {'LEMMA': 'filter'}]