The canny detector with edge region focusing using an anisotropic diffusion process

Galvanin, Edinéia Aparecida dos Santos; Vale, Giovane Maia do; Póz, Aluir Porfírio Dal

doi:10.1134/s1054661806040067

Cited by 14 publications

(7 citation statements)

References 4 publications

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“…When k=1, the functions of the two   is very large, indicating the strengthening of diffusion. By this method, the different parts of the image can be smoothed accordingly [7]. In Figure 1, it is easy to observe that u  is enlarging, and at the edge, Formula 9 closes to 0 with faster speed than Formula 10.…”

Section:  mentioning

confidence: 99%

“…When using the traditional Canny operator to detect the edge, it's a must to set the high and low thresholds manually [7]. As the threshold has great influence on the results of the edge detection, for achieving the best edge detection results, the threshold should be selected accordingly based on the images, which troubles the edge detection as well.…”

Section: The Self-adaptive Selection Of the Thresholdmentioning

confidence: 99%

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Canny Optimization Algorithm Based on Improved Anisotropic Diffusion Function Filtering

Zhang¹,

Zhang²

2016

IJSIP

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Image edge detection is an important part of image processing, and the effect of edge detection is also directly affected by image analysis, recognition and understanding. Canny operator is the most commonly used image edge detection operator. However, this operator has some limitations. The traditional Canny operator uses Gaussian filtering which may bring problems such as missing edge information and false edge. Besides, the selection of high and low thresholds of the traditional Canny operator are not accurate, and cannot be carried out by self-adaption. In order to solve these problems, this paper presents an optimized algorithm for Canny operator. In this paper, an improved anisotropic diffusion function is used to filter the image, and the improved filtering not only reduces the noise, but also maintains the edge information of the image. Additionally, this paper has improved the maximum between-class variance method (OTSU) to select the high and low thresholds of Canny operator by self-adaption. The improved algorithm is applied to edge detection of various images, and the results indicated that the improved Canny operator is effective in reducing noise and extracting edge.

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Section:  mentioning

confidence: 99%

Section: The Self-adaptive Selection Of the Thresholdmentioning

confidence: 99%

Canny Optimization Algorithm Based on Improved Anisotropic Diffusion Function Filtering

Zhang¹,

Zhang²

2016

IJSIP

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“…The outputs of edge detectors, namely edge maps, are the foundation of high-level image processing, such as object tracking [1], image segmentation [2] and corner detection [3]. Various methods have been developed, including the differentiation-based methods [4][5][6][7], statistical methods [8,9], machine learning methods [10,11], active contour method [12], multiscale methods [13][14][15][16][17][18][19], and the anisotropic diffusion or selective smoothing methods [20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

“…Various anisotropic diffusion or selective smoothing methods based upon PDE were developed for image denoising, edge detection, and segmentation [22][23][24]. The anisotropic diffusion based upon partial differential equation (PDE) provides an iterative and adaptive Gaussian smoothing of images, where the kernels are matched to the micro-local structures around each pixel in scales and directions.…”

Section: Introductionmentioning

confidence: 99%

“…The anisotropic diffusion based upon partial differential equation (PDE) provides an iterative and adaptive Gaussian smoothing of images, where the kernels are matched to the micro-local structures around each pixel in scales and directions. The anisotropic diffusion based upon PDE realizes edge region focusing before detection and the followed Canny-type operator performs edge extraction from smoothed images [24]. It is noticed that iterative and adaptive smoothing algorithms are computationally expensive and the corresponding edge detectors are not fast in implementation.…”

Section: Introductionmentioning

confidence: 99%

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Noise robust image edge detection based upon the automatic anisotropic Gaussian kernels

Zhang

Zhao

Breckon

et al. 2017

Pattern Recognition

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Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. Gaussian kernels (ANGKs), which also addresses the current problem that the seminal Canny edge detector may miss some obvious crossing edge details. Firstly, automatic ANGKs are designed according to the noise suppression, edge resolution and localization precision, which also conciliate the conflict between them. Secondly, reasons why cross-edge points are missing from Canny detector results using isotropic Gaussian kernel are analyzed. Thirdly, the automatic ANGKs are used to smooth image and a revised edge extraction method is used to extract edges. Finally, the aggregate test receiver-operating-characteristic (ROC) curves and Pratt's Figure of Merit (FOM) are used to evaluate the proposed detector against state-of-the-art edge detectors. The experiment results show that the proposed algorithm can obtain better performance for noise-free and noisy images.

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An image edge recognition approach based on multi-operator dynamic weight detection in virtual reality scenario

Yu-jing

Dong

2018

Cluster Comput

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The canny detector with edge region focusing using an anisotropic diffusion process

Cited by 14 publications

References 4 publications

Canny Optimization Algorithm Based on Improved Anisotropic Diffusion Function Filtering

Canny Optimization Algorithm Based on Improved Anisotropic Diffusion Function Filtering

Noise robust image edge detection based upon the automatic anisotropic Gaussian kernels

An image edge recognition approach based on multi-operator dynamic weight detection in virtual reality scenario

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