Adaptive Image Edge Extraction Based on Discrete Algorithm and Classical Canny Operator

Kanchanatripop, Phusit; Zhang, Dafang

doi:10.3390/sym12111749

Cited by 16 publications

(13 citation statements)

References 18 publications

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“…The main method is to make the weighted difference between the gray values of the upper, lower, left and right fields of the target pixels, and then smooth the image. The greater the weight close to the target pixel, the greater the impact on the target during convolution [13][14]. The steps of the Sobel operator to determine the image edge are as follows: www.ijacsa.thesai.org…”

Section: Principle Of Sobel Edge Detectionmentioning

confidence: 99%

Sobel Edge Detection Algorithm with Adaptive Threshold based on Improved Genetic Algorithm for Image Processing

Kong¹,

Chen²,

Song³

et al. 2023

IJACSA

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In this paper, a novel adaptive threshold Sobel edge detection algorithm based on the improved genetic algorithm is proposed to detect edges. Because of the influence of external factors in actual detection process, the result of detection is often not accurate enough when the configured threshold of the target image is far away from the real threshold. Different thresholds of images are calculated by improved genetic algorithm for different images. The calculated threshold is used in edge detection. The experimental results show that the image processed by the improved algorithm has stronger edge continuity. It is shown that proposed algorithm has a better detection effect and applicability than the traditional Sobel algorithm.

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Section: Principle Of Sobel Edge Detectionmentioning

confidence: 99%

Sobel Edge Detection Algorithm with Adaptive Threshold based on Improved Genetic Algorithm for Image Processing

Kong¹,

Chen²,

Song³

et al. 2023

IJACSA

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“…The LOG operator has better scale characteristics than the other operators and has both filtering and edge detection for a detected image, which can ensure a better balance between detection and localization errors. The COG operator introduces a Gaussian filtering function, which has a significant noise suppression effect, is sensitive to pseudoedges, and provides more refined detection results [65,66].…”

Section: Edge Information Extraction For the Yellow River At The Nort...mentioning

confidence: 99%

How Can We Understand the Past from Now On? Three-Dimensional Modelling and Landscape Reconstruction of the Shuanghuaishu Site in the Central Plains of China

et al. 2022

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The Shuanghuaishu (SHS) site in China is one of the 100 most important archaeological discoveries over the past 100 years; its historical heritage can be traced directly back 5300 years. Understanding the early landscape of the site would provide important information about the origin of Chinese civilization. The SHS site is buried and surface traces are difficult to see; therefore, we attempted to reconstruct the early landscape of the site based on a current surface landscape model and environmental archaeological analysis. We created a modern three-dimensional (3D) landscape model of the study area from high spatial resolution unmanned aerial vehicle (UAV) aerial photographs and analysed the distance change between the Yellow River and SHS site in the past 60 years from CORONA and Landsat images. By combining environmental archaeological survey results, archaeological excavation data, relevant papers, and field measurements, we reconstructed the paleotopography of the SHS site during the Yangshao period (7000–5000 aBP). On this basis, 3D natural and human landscapes during the Yangshao period were rebuilt. The results show that (1) Satellite images acquired at different resolutions can provide multiscale spatial information about the site, and high-precision models of current conditions can be quickly generated from UAV aerial photography. (2) From 1960 to 2020, the shortest distance between the SHS site and the Yellow River was approximately 512 m. The location of bedrock on Mang Mountain can be used to infer the early extent of the northern terrace at the site. (3) Environmental archaeology provided information about the palaeoenvironment of the site area. By incorporating spatial information technology and 3D visualization, we can better restore the early landscape of the SHS site. Our work integrates environmental archaeology, field archaeology, and spatial technology, enabling data and modelling support for the visual interpretation of the SHS site.

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“…Since the grey value in the gradient direction must be monotonically decreasing and the sub-pixel edge points are the points where the grey value changes most significantly in the gradient direction, the sub-pixel edge points must follow two principles [20]:…”

Section: Sub-pixel Level Edge Measurement Algorithm Based On Cubic Spline Interpolationmentioning

confidence: 99%

Research on O-ring Dimension Measurement Algorithm Based on Cubic Spline Interpolation

Zheng

Yin

et al. 2021

Applied Sciences

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Current O-ring dimension measurement algorithms based on machine vision are mainly whole-pixel level algorithms, which have the disadvantage of a low measurement accuracy. In order to improve the stability and accuracy of O-ring dimension measurement, a sub-pixel edge detection algorithm based on cubic spline interpolation is proposed for O-ring dimension measurement. After image pre-processing of the O-ring graphics, the whole-pixel-level O-ring edges are obtained by using a noise-resistant mathematical morphology method, and then the sub-pixel edge contours are obtained using a sub-pixel edge detection algorithm based on cubic spline interpolation. Finally, the edge curve is fitted with the least squares method to obtain its inner and outer diameter as well as the size of the wire diameter. The experimental data show that the algorithm has a mean square error of 4.8 μm for the outer diameter and 0.18 μm for the wire diameter. The outer diameter error is kept within ± 100 μm and the wire diameter error can be kept within ±15 μm. Compared with the whole pixel algorithm, the measurement accuracy has been greatly improved.

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Adaptive Image Edge Extraction Based on Discrete Algorithm and Classical Canny Operator

Cited by 16 publications

References 18 publications

Sobel Edge Detection Algorithm with Adaptive Threshold based on Improved Genetic Algorithm for Image Processing

Sobel Edge Detection Algorithm with Adaptive Threshold based on Improved Genetic Algorithm for Image Processing

How Can We Understand the Past from Now On? Three-Dimensional Modelling and Landscape Reconstruction of the Shuanghuaishu Site in the Central Plains of China

Research on O-ring Dimension Measurement Algorithm Based on Cubic Spline Interpolation

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