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Journal articles on the topic 'Canny edge detection algorithm'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

S, Britto Ramesh Kumar, and Bhuvaneshwari A. "AN EFFICIENT BRITWARI TECHNIQUE TO ENHANCE CANNY EDGE DETECTION ALGORITHM USING DEEP LEARNING." ICTACT Journal on Soft Computing 12, no. 3 (2022): 2634–39. http://dx.doi.org/10.21917/ijsc.2022.0377.

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Artificial Intelligence edge detection refers to a set of mathematical techniques used to recognize digital image locations. The picture brightness plays a vital role in detecting dissimilarities and making decisions. Edges are the sharp changes in pictures with respect to the brightness and are commonly categorized into a collection of curved line segments. The main focus of this paper is to find sharp corner edges and the false edges present in the MRI images. The canny edge algorithm is a popular method for detecting these types of edges. The traditional canny edge detection technique has v

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Agrawal, Himangi, and Krish Desai. "CANNY EDGE DETECTION: A COMPREHENSIVE REVIEW." International Journal of Technical Research & Science 9, Spl (2024): 27–35. http://dx.doi.org/10.30780/specialissue-iset-2024/023.

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Canny edge detection is a widely employed technique in image processing known for its effectiveness in identifying and highlighting edges within digital images. Because of its excellent performance, the Canny Edge Detector is one of the most used edge detection algorithms. For several image processing techniques, including image enhancement, image segmentation, tracking, and image/video coding, edge detection serves as a preliminary step. Compared to the Sobel algorithm, Canny's edge detection approach yields much lower memory requirements, reduced latency, and enhanced throughput without sacr

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Ramgundewar, Pallavi, S. P. Hingway, and K. Mankar. "Design of Modified Canny Edge Detector Based on FPGA for Portable Device." Journal of Advance Research in Electrical & Electronics Engineering (ISSN: 2208-2395) 2, no. 7 (2015): 06–11. http://dx.doi.org/10.53555/nneee.v2i7.184.

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Edge detection is one of the key stages in image processing and object reorganization. The Canny Edge Detector is one of the most widely used edge detection algorithm due to its superior performance. In this paper, we propose a mechanism to implement the Canny algorithm at the block level without any loss in edge detection performance compared with the original frame-based Canny algorithm. Directly applying the original Canny Edge detection algorithm at the blocklevel leads to excessive edges in smooth regions and to loss of significant edges in high-detailed regions since the original Canny c

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Chhetri, Chhetra Bahadur, and Manish Pandey. "Performance Evaluation of Different Images Using Edge Detection Algorithms." National College of Computer Studies Research Journal 2, no. 1 (2023): 34–48. http://dx.doi.org/10.3126/nccsrj.v2i1.60053.

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To determine which edge detection method performs best and worst on different image types, numerous edge detection algorithms are examined. For the performance analysis, some sample photos from the web and some from Java are used as sources. The entropy and signal noise ratio are used to gauge how well the edged image performs. In image processing, conducting a thorough investigation of various edge detection techniques is highly worthwhile two widely used edge detection algorithms Log, and Canny—are taken into consideration in this analysis. Here in this paper, the analysis is focused on the

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Karthick, C. N., and P. Nirmala. "Smart Edge Detection Technique in X ray Images for Improving PSNR using Canny Edge Detection Algorithm with Gaussian Filter in Comparison with Laplacian Algorithm." CARDIOMETRY, no. 25 (February 14, 2023): 1744–50. http://dx.doi.org/10.18137/cardiometry.2022.25.17441750.

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Aim: The aim of this study is to propose smart edge detection techniques in x-ray images for improving PSNR using canny edge detection algorithm and compared with laplacian algorithm. Materials and Methods: Using the design of edge detection technique and to improve PSNR, canny edge detection algorithm is used along with gaussian filter and it is compared with laplacian algorithm. Canny edge detection algorithm and laplacian algorithm are the two groups considered in this study. For each group the sample size is 20 and the total sample size is 40. Sample size calculation was done using clinica

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Cao, Jianfang, Lichao Chen, Min Wang, and Yun Tian. "Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform." Computational Intelligence and Neuroscience 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/3598284.

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The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator’s dual threshold and improve the edge detection performance, while the Map

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Kieu, S. T. H., A. Bade, and M. H. A. Hijazi. "Modified canny edge detection technique for identifying endpoints." Journal of Physics: Conference Series 2314, no. 1 (2022): 012023. http://dx.doi.org/10.1088/1742-6596/2314/1/012023.

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Abstract Edge detection is an image processing technique that retains the edges of an object in an image while discarding other features. The Canny edge detection technique is regarded as one of the most successful edge detection algorithms because of the good edge detection effect. However, one of its problems is the discontinued edges. In this paper, we present an endpoint identification algorithm that can pinpoint the position of the discontinued edges. After the endpoints are identified, they are paired together based on distance, and the broken gaps are filled by connecting the endpoints.

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M. Almufti, Saman. "Hybridizing Ant Colony Optimization Algorithm for Optimizing Edge-Detector Techniques." Academic Journal of Nawroz University 11, no. 2 (2022): 135–45. http://dx.doi.org/10.25007/ajnu.v11n2a1320.

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Ant colony optimization is a swarm intelligent algorithm that mimics the ant behaviors to optimize solutions for hard optimization problems. Over years Ant-based algorithms have been used in solving different problems including: Traveling Salesman Problem (TSP), Wireless Sensors Network (WSN), Benchmark Problem, and it has been used in various image processing applications. In the image processing fields various techniques have been used to detect edges in a digital image such as Canny and Sobel edge detectors. This Study, proposed a hybridized Ant Colony Optimization algorithm for optimizing

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9

Supriyatin, Wahyu. "Perbandingan Metode Sobel, Prewitt, Robert dan Canny pada Deteksi Tepi Objek Bergerak." ILKOM Jurnal Ilmiah 12, no. 2 (2020): 112–20. http://dx.doi.org/10.33096/ilkom.v12i2.541.112-120.

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Computer vision is one of field of image processing. To be able to recognize a shape, it requires the initial stages in image processing, namely as edge detection. The object used in tracking in computer vision is a moving object (video). Edge detection is used to recognize edges of objects and reduce existing noise. Edge detection algorithms used for this research are using Sobel, Prewitt, Robert and Canny. Tests were carried out on three videos taken from the Matlab library. Testing is done using Simulik Matlab tools. The edge and overlay test results show that the Prewitt algorithm has bett

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Hamdani, Ibnu Mansyur, Ismi Rizqa Lina, and Muhammad Takdir Muslihi. "Deteksi Tepi Optimal dengan Integrasi Canny, CLAHE, dan Perona-Malik Diffusion Filter." Jurnal Mosfet 5, no. 1 (2025): 127–36. https://doi.org/10.31850/jmosfet.v5i1.3638.

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Edge detection is a fundamental technique in digital image processing, crucial for identifying object boundaries. However, detecting edges in low-intensity and noisy images remains a significant challenge. This study proposes an optimal edge detection method by integrating the Canny algorithm, Contrast Limited Adaptive Histogram Equalization (CLAHE), and Perona-Malik Diffusion Filter, with automatic kappa (k) value determination using the Fractional Order Sobel Mask. The process begins with noise reduction through the Perona-Malik Diffusion Filter, followed by local contrast enhancement using

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Wang, Zhicheng, Zhe Wang, Nanhai Huang, and Jie Zhao. "An Improved Canny-Zernike Subpixel Detection Algorithm." Wireless Communications and Mobile Computing 2022 (June 20, 2022): 1–7. http://dx.doi.org/10.1155/2022/1488406.

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This paper proposed a new subpixel detection method that detects subpixel edges directly, as opposed to the previous method, which requires crossing the entire image. It shows superior subpixel detection on the edge directly, which enhances subpixel edge detection speed significantly. In order to overcome the problem of noise reduction, this paper employs bilateral filtering. The method first performed coarse localization with the improved operator to determine the coordinates and gradient direction of the edge points. Then, the Zernike moment algorithm was used for subpixel repositioning of e

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Jayasree, M., K. Narayanan N, V. Kabeer, and C. R. Arun. "An Enhanced Block Based Edge Detection Technique Using Hysteresis Thresholding." Signal & Image Processing : An International Journal (SIPIJ) 9, no. 2 (2019): 15–26. https://doi.org/10.5281/zenodo.3248683.

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Edge detection is a crucial step in various image processing systems like computer vision , pattern recognition and feature extraction. The Canny edge detection algorithm even though exhibits high accuracy, is computationally more complex compared to other edge detection techniques. A block based distributed edge detection technique is presented in this paper, which adaptively finds the thresholds for edge detection depending on block type and the distribution of gradients in each block. A novel method of computation of high threshold has been proposed in this paper. Block-based hysteresis thr

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Tengku Alang, Tengku Ahmad Iskandar, Tan Tian Swee, Tan Jia Hou, et al. "Global Canny algorithm based on Canny edge detector framework in magnetic resonance imaging." Malaysian Journal of Fundamental and Applied Sciences 13, no. 4-2 (2017): 445–51. http://dx.doi.org/10.11113/mjfas.v13n4-2.761.

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Magnetic resonance imaging is an important modality in the diagnosis and pathology detection. Edge detection is used for image segmentation and feature extraction as part of the medical image analysis. There is no ideal and universal algorithm which performs perfectly under all conditions. Conventional Canny edge detector is not suitable to be used in Magnetic resonance images that contaminated by Rician noise. In this paper, we propose the use of customized non-local means into the Canny edge detector instead of Gaussian smoothing in the conventional Canny edge detector to effectively remove

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Mole S S, Sreeja. "RAPID BLEEDING REGION DETECTION IN WIRELESS CAPSULE ENDOSCOPY VIDEOS." JOURNAL OF ADVANCES IN CHEMISTRY 13, no. 8 (2017): 6389–92. http://dx.doi.org/10.24297/jac.v13i8.5757.

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Wireless Capsule Endoscopy (WCC) is a medical imaging technique used to examine parts of the gastrointestinal tract. Computer aided detection is used to increase the speed of detection, better performance and reduce the time. Before finding the bleeding regions the edge regions are first detected and removed. Both the edge and the bleeding regions will share the same Hue value and the luminance should be same for the bleeding and the non -bleeding regions .We use a canny edge detector operator for detecting the edge regions in L channel. Canny edge detector is used to detect more edge pixels a

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Deokar, Poonam S., and Anagha P. Khedkar. "SURVEY ON DISTRIBUTED CANNY EDGE DETECTOR WITH FPGA." International Journal of Research -GRANTHAALAYAH 3, no. 3 (2015): 51–61. http://dx.doi.org/10.29121/granthaalayah.v3.i3.2015.3031.

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The Edge can be defined as discontinuities in image intensity from one pixel to another. Modem image processing applications demonstrate an increasing demand for computational power and memories space. Typically, edge detection algorithms are implemented using software. With advances in Very Large Scale Integration (VLSI) technology, their hardware implementation has become an attractive alternative, especially for real-time applications. The Canny algorithm computes the higher and lower thresholds for edge detection based on the entire image statistics, which prevents the processing of blocks

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Poonam, S. Deokar, and P. Khedkar Anagha. "SURVEY ON DISTRIBUTED CANNY EDGE DETECTOR WITH FPGA." International Journal of Research - GRANTHAALAYAH 3, no. 3 (2017): 51–61. https://doi.org/10.5281/zenodo.883963.

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The Edge can be defined as discontinuities in image intensity from one pixel to another. Modem image processing applications demonstrate an increasing demand for computational power and memories space. Typically, edge detection algorithms are implemented using software. With advances in Very Large Scale Integration (VLSI) technology, their hardware implementation has become an attractive alternative, especially for real-time applications. The Canny algorithm computes the higher and lower thresholds for edge detection based on the entire image statistics, which prevents the processing of blocks

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17

Song, Renjie, Ziqi Zhang, and Haiyang Liu. "Edge connection based Canny edge detection algorithm." Pattern Recognition and Image Analysis 27, no. 4 (2017): 740–47. http://dx.doi.org/10.1134/s1054661817040162.

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18

Yu, Kun Lin, and Zhi Yu Xie. "Polynomial Interpolation Sub-Pixel Edge Detection Method Based on Improved Canny Operator." Applied Mechanics and Materials 563 (May 2014): 203–7. http://dx.doi.org/10.4028/www.scientific.net/amm.563.203.

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According to the shortcoming of traditional Canny edge detection algorithm is sensitive to noise and low positioning accuracy, this paper proposes an algorithm of Polynomial interpolation Sub-pixel edge detection based on improved Canny operator: We first use improved Canny operator edge detection algorithm to extract rough image edge, then use the quadratic Polynomial interpolation to calculate on the rough extraction edge, finally refine the edge image. Experiments show that the improved method is better than the traditional detection method can accurately locate the image edge.

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Zou, Lin, Yunlong Zheng, and Jie Lu. "An Edge Detection Method for Welding Pool Based on An Improved Canny Algorithm." Journal of Physics: Conference Series 2785, no. 1 (2024): 012013. http://dx.doi.org/10.1088/1742-6596/2785/1/012013.

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Abstract In this study, an improved Canny algorithm is proposed for detecting welding pool edges in complex environments, considering the issues of inaccurate extraction, discontinuity, and susceptibility to noise in traditional edge detection algorithms. Firstly, the original Gaussian filter is replaced with a hybrid filter that combines dark channel prior defogging and bilateral filtering used for image denoising. Then, a four-direction Sobel operator is utilized to calculate gradient amplitude and direction. Furthermore, the double threshold required for extracting and connecting pool edges

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Huang, Ying, Qi Pan, Qi Liu, Xin Peng He, Yun Feng Liu, and Yong Quan Yu. "Application of Improved Canny Algorithm on the IC Chip pin Inspection." Advanced Materials Research 317-319 (August 2011): 854–58. http://dx.doi.org/10.4028/www.scientific.net/amr.317-319.854.

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Machine vision is widely used in chip pin automation detection of defects, the accuracy of image edge extraction for detection result has very big effect. Canny edge detection algorithm is a kind of edge detection algorithm which have good comprehensive evaluation, but the Gaussian filter algorithm it used may cause image too smooth and fuzzy of the edge, and it is very sensitive for impulse noise. This paper discusses the improved methods of Canny, proposes an improved switch median filter algorithm, which is applied into Canny algorithm, makes the edge of IC Chip pin more complete and remove

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Ma, Zhan Chun, and Xiao Mei Ning. "A Novel Edge Detection Algorithm for Medical Image." Applied Mechanics and Materials 151 (January 2012): 653–56. http://dx.doi.org/10.4028/www.scientific.net/amm.151.653.

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CANNY operator had widely usage for edge detection; however it also had certain deficiencies. So the traditional CANNY operator about this is improved and puts forward a kind of new algorithm used for image edge detection. Compared improved algorithm with traditional algorithm for edge detection, simulations shows that new algorithm is more effective for image edge detection and the clearer detection result is obtained.

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22

Yujie, Wang. "A comparison of canny edge detection algorithm and edge detection algorithm based on fuzzy logic." Applied and Computational Engineering 4, no. 1 (2023): 780–85. http://dx.doi.org/10.54254/2755-2721/4/2023422.

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Edge detection techniques in digital image processing are a very valuable area of research. In recent years, there are two more popular edge detection algorithms, one is Canny edge detection algorithm,and the other is edge detection algorithm based on Fuzzy Logic. Both algorithms have been used in various fields. The main work of this paper is to do a brief introduction of two algorithms and compare the results from them.

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Li, Qinghua, Wanting Zhao, Siyuan Cheng, and Yi Ji. "Research on Concentricity Detection Method of Automobile Brake Piston Parts Based on Improved Canny Algorithm." Applied Sciences 15, no. 8 (2025): 4397. https://doi.org/10.3390/app15084397.

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The automotive brake piston component is an important part of the automotive brake system, and the concentricity detection of the first piston component is crucial to ensure driving safety. In this paper, an improved Canny algorithm is proposed for non-contact detection of spring concentricity of the first piston component. Firstly, the traditional Canny algorithm is improved by replacing the Gaussian filter with a bilateral filter to fully retain the edge information, and accurate edge detection results are obtained by constructing a multi-scale analysis. After obtaining the edge images, a su

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Chao, Yuan, Fan Shi, Wentao Shan, and Dong Liang. "Edge Location and Identification Method for Electronic Components based on Improved Canny Algorithm." International Journal of Circuits, Systems and Signal Processing 16 (January 10, 2022): 209–14. http://dx.doi.org/10.46300/9106.2022.16.25.

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The position identification of SMD electronic components mainly uses Canny edge detection algorithm to detect the edges of specific elements, benefited from its computational simplicity. The traditional Canny algorithm lacks the adaptability in gradient calculation and double thresholds selection, which may affect the location and identification accuracy of specific elements in electronic components. In this paper, an improved canny edge detection algorithm is proposed. The gradient magnitude is calculated in four directions, i.e., horizontal, vertical, and diagonal. Both the high and low thre

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Song, Yupu, Cailin Li, Shiyang Xiao, Qinglei Zhou, and Han Xiao. "A parallel Canny edge detection algorithm based on OpenCL acceleration." PLOS ONE 19, no. 1 (2024): e0292345. http://dx.doi.org/10.1371/journal.pone.0292345.

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In the process of Canny edge detection, a large number of high complexity calculations such as Gaussian filtering, gradient calculation, non-maximum suppression, and double threshold judgment need to be performed on the image, which takes up a lot of operation time, which is a great challenge to the real-time requirements of the algorithm. The traditional Canny edge detection technology mainly uses customized equipment such as DSP and FPGA, but it has some problems, such as long development cycle, difficult debugging, resource consumption, and so on. At the same time, the adopted CUDA platform

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Akbari Sekehravani, Ehsan, Eduard Babulak, and Mehdi Masoodi. "Implementing canny edge detection algorithm for noisy image." Bulletin of Electrical Engineering and Informatics 9, no. 4 (2020): 1404–10. http://dx.doi.org/10.11591/eei.v9i4.1837.

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Edge detection is a significant stage in different image processing operations like pattern recognition, feature extraction, and computer vision. Although the Canny edge detection algorithm exhibits high precision is computationally more complex contrasted to other edge detection methods. Due to the traditional Canny algorithm uses the Gaussian filter, which gives the edge detail represents blurry also its effect in filtering salt-and-pepper noise is not good. In order to resolve this problem, we utilized the median filter to maintain the details of the image and eliminate the noise. This pape

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Ehsan, Akbari Sekehravani, Babulak Eduard, and Masoodi Mehdi. "Implementing canny edge detection algorithm for noisy image." Bulletin of Electrical Engineering and Informatics 9, no. 4 (2020): 1404–10. https://doi.org/10.11591/eei.v9i4.1837.

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Edge detection is a significant stage in different image processing operations like pattern recognition, feature extraction, and computer vision. Although the Canny edge detection algorithm which exhibits high precision is computationally more complex contrasted to other edge detection methods. Due to the traditional Canny algorithm uses the Gaussian filter, which gives the edge detail represents blurry also its effect in filtering salt-and-pepper noise is not good. To resolve this problem, we utilized the median filter to maintain the details of the image and eliminate the noise. This paper p

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Gunawan, Teddy Surya, Iza Zayana Yaacob, Mira Kartiwi, Nanang Ismail, Nor Farahidah Za'bah, and Hasmah Mansor. "Artificial Neural Network Based Fast Edge Detection Algorithm for MRI Medical Images." Indonesian Journal of Electrical Engineering and Computer Science 7, no. 1 (2017): 123. http://dx.doi.org/10.11591/ijeecs.v7.i1.pp123-130.

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<p>Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. Edges are represented as important contour features in the medical image since they are the boundaries where distinct intensity changes or discontinuities occur. Many traditional algorithms have been proposed to detect the edge, such as Canny, Sobel, Prewitt, Roberts, Zerocross, and Laplacian of Gaussian (LoG). Moreover, many researches have shown the potential of using Artificial Neural Network (ANN) for edge detection. A

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Damanik, Romanus. "IMAGE DETECTION EDGE IMAGE USING CANNY EDGE ALGORITHM." Journal of Artificial Intelligence and Engineering Applications (JAIEA) 1, no. 3 (2022): 248–55. http://dx.doi.org/10.59934/jaiea.v1i3.109.

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In general, edge detection is widely used in image processing to find the boundaries of objects in an image. In this study, a technique for detecting edges that is commonly used will be studied, namely the Canny method under different conditions using Visual Studio software. In the testing process that the author carried out, it was concluded that sooner or later a process of converting an object would be, that the following factors affect the conversion process, including; type of image, image resolution, image format, specifications of the camera used to take pictures as well as the specific

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Sun, Tao, and Chang Zhi Gao. "An Improved Canny Edge Detection Algorithm." Applied Mechanics and Materials 291-294 (February 2013): 2869–73. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2869.

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Traditional Canny edge detection algorithm uses a global threshold selection method, when large changes are in the background of the image and the target gray, global threshold method may lose some local edge information. For this problem, this paper therefore proposes an adaptive dynamic threshold improved Canny edge detection algorithm. The method uses image gradient variance as the criterion of the image block according to the four forks tree principle, then uses the Otsu method to get the corresponding sub-block threshold value for each sub-block, and obtains threshold value matrix by inte

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Chen, Yu, Caixia Deng, and Xiaxia Chen. "An Improved Canny Edge Detection Algorithm." International Journal of Hybrid Information Technology 8, no. 10 (2015): 359–70. http://dx.doi.org/10.14257/ijhit.2015.8.10.33.

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Liu, Ruiyuan, and Jian Mao. "Research on Improved Canny Edge Detection Algorithm." MATEC Web of Conferences 232 (2018): 03053. http://dx.doi.org/10.1051/matecconf/201823203053.

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Aiming at the poor noise robustness of traditional Canny algorithm and the defect of false edge or edge loss, an edge detection algorithm using statistical algorithm for filtering denoising and using genetic algorithm to determine the optimal high and low threshold of image segmentation is proposed. Firstly, statistical filtering uses mean and variance to denoise, avoiding the problem of Gaussian denoising susceptible to interference in the traditional Canny algorithm, and ensuring the integrity of image edge information. Secondly, this article uses the genetic algorithm, design the crossover

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Zhang, Dan Dan, and Shuang Zhao. "An Improved Edge Detection Algorithm Based on Canny Operator." Applied Mechanics and Materials 347-350 (August 2013): 3541–45. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.3541.

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The traditional Canny edge detection algorithm is analyzed in this paper. To overcome the difficulty of threshold selecting in Canny algorithm, an improved method based on Otsu algorithm and mathematical morphology is proposed to choose the threshold adaptively and simultaneously. This method applies the improved Canny operator and the image morphology separately to image edge detection, and then performs image fusion of the two results using the wavelet fusion technology to obtain the final edge-image. Simulation results show that the proposed algorithm has better anti-noise ability and effec

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Suhail Ahamed. T, Anitha G. "Enhancing Water Body Identification in Satellite Images through Comparative Analysis of Canny Edge Detection and Scale-Invariant Feature Transform Algorithms." Tuijin Jishu/Journal of Propulsion Technology 44, no. 3 (2023): 433–38. http://dx.doi.org/10.52783/tjjpt.v44.i3.296.

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Aim: The objective of this research is to utilize the Innovative Canny Edge Detection algorithm to precisely identify water bodies in satellite images acquired from the Water Access program. Subsequently, the performance of this approach will be evaluated by comparing it with the SIFT algorithm. The primary objective of this analysis is to contribute to the equilibrium of the water ecosystem. Materials and Methods: Within this study, two distinct groups were compared: the Innovative Canny Edge Detection algorithm (CED) (N=10) and the scale invariant feature transform algorithm (SIFT) (N=10). T

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Qian, Yue Jing, and Yuan Fan. "Rice Edges Detection Based on Canny Operator." Advanced Materials Research 542-543 (June 2012): 1302–5. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.1302.

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Rice edge detection is the first step on obtaining rice image feature. In this paper, an improved Canny edge detection algorithm was represented to obtain thin and robust rice edges. Firstly, nonlinear diffusion filter was used to wipe of noise efficiently and kept the edge information of the image. Secondly, gradient calculation of pixel diagonal direction was considered in the calculation of neighborhood gradient amplitude which further repressed the impact of noise. Thirdly, using average interclass variance could self-adaptively calculate the double thresholds for different images. The res

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KAUR, AMANDEEP, and CHANDAN SINGH. "A HYBRID EDGE DETECTOR USING FUZZY LOGIC AND MATHEMATICAL MORPHOLOGY." International Journal of Image and Graphics 10, no. 02 (2010): 251–72. http://dx.doi.org/10.1142/s0219467810003767.

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Edge detection concerns the localization of significant variations of the grey level image. Detection of edges in an image is very important step for a complete image understanding system. This paper proposes a new approach to edge detection which adopts fuzzy reasoning to detect edges and mathematical morphology for edge thinning. The results achieved by this algorithm are comparable to the Canny approach. In Canny edge detector we may require many runs using different combinations of the three parameters (two threshold and one sigma values) whereas in the proposed technique only one paramete

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Yadav, Dhirendra Prasad, Ashish Sharma, Senthil Athithan, Abhishek Bhola, Bhisham Sharma, and Imed Ben Dhaou. "Hybrid SFNet Model for Bone Fracture Detection and Classification Using ML/DL." Sensors 22, no. 15 (2022): 5823. http://dx.doi.org/10.3390/s22155823.

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An expert performs bone fracture diagnosis using an X-ray image manually, which is a time-consuming process. The development of machine learning (ML), as well as deep learning (DL), has set a new path in medical image diagnosis. In this study, we proposed a novel multi-scale feature fusion of a convolution neural network (CNN) and an improved canny edge algorithm that segregate fracture and healthy bone image. The hybrid scale fracture network (SFNet) is a novel two-scale sequential DL model. This model is highly efficient for bone fracture diagnosis and takes less computation time compared to

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Samuel, Moveh, Maziah Mohamad, Shaharil Mad Saad, and Mohamed Hussein. "Development of Edge-Based Lane Detection Algorithm using Image Processing." JOIV : International Journal on Informatics Visualization 2, no. 1 (2018): 19. http://dx.doi.org/10.30630/joiv.2.1.101.

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Image processing is known as the process of converting an image into a digital form so as to obtain an enhanced image and to extract useful information from it. This paper presents a simple step by step analysis of edges-based lane detection. Some of the known and common edge detection techniques such as Sobel, Canny, Prewitt and Roberts were studied and evaluated using image segmentation, morphology, image statistic and Hough Transform. The result indicated some similarities in the process as well as major differences. These differences were observed to be as a result of the high sensitivity

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Sundari M, Vana. "VLSI Architecture Design and Implementation of CANNY Edge Detection." Journal of University of Shanghai for Science and Technology 24, no. 02 (2022): 200–208. http://dx.doi.org/10.51201/jusst/22/0167.

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In One of the most essential methods in digital image processing is edge detection. Because of its capacity to detect edges even in images heavily contaminated by noise, the Canny edge detector is the most widely used edge detection algorithm. A modified canny edge detector is created in MATLAB and implemented in FPGA in this project. The mask is used for gradient calculation, and bilinear interpolation of four pixels is used in non-maximal suppression. In the iris detection subsystem, this edge detector is used as a pre-processing stage. The goal of creating the hardware modules for the canny

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Chen, Xue Fang, Hao Bing Guan, Ji Nan Gu, and Qian Wu. "A Study and Improvements on Canny Algorithm." Advanced Engineering Forum 6-7 (September 2012): 205–9. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.205.

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This paper studies principle of the traditional Canny edge detection algorithm and the existing problems. Some solutions toward the problems are also proposed. The improvement methods consisted of two parts. On the one hand, as Canny edge algorithm itself does not have strong noise immunity while ensuring edge positioning accuracy, an adaptive median filter denoising program based on the Canny Gaussian filter is proposed to enhance the Canny algorithm filter performance. On the other hand, given the Canny algorithm high and low threshold parameter is not determined by the feature information o

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Miao, Jia Qing. "Based on Canny Operator with Regional Growth Combined Research on Accurate Image Segmentation Algorithm." Advanced Materials Research 989-994 (July 2014): 2088–92. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2088.

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In this paper, first we introduce the digital image algorithm of Canny edge detection, and then simulation results of Canny edge detection are given particularly. Test results show that the improved algorithm improves the accuracy of edge detection effectively. Secondly, the algorithm of the region growth, which algorithm is divided into two parts: one is growing region; the other is merging region, is realized. Finally, based on above analysis, we find out that a continuous boundary is not obtained by edge detection, and the method of regional extraction may produce transition segmentation. I

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Jeyaraman, Gowri, and Janakiraman Subbiah. "An Edge Exposure using Caliber Fuzzy C-means With Canny Algorithm." Indonesian Journal of Electrical Engineering and Computer Science 8, no. 1 (2017): 59. http://dx.doi.org/10.11591/ijeecs.v8.i1.pp59-68.

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<p>Edge exposure or edge detection is an important and classical study of the medical field and computer vision. Caliber Fuzzy C-means (CFCM) clustering Algorithm for edge detection depends on the selection of initial cluster center value. This endeavor to put in order a collection of pixels into a cluster, such that a pixel within the cluster must be more comparable to every other pixel. Using CFCM techniques first cluster the BSDS image, next the clustered image is given as an input to the basic canny edge detection algorithm. The application of new parameters with fewer operations for

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Wang, Zhenyu, Mingshun Yang, Leijie Ren, et al. "An Improved BM3D-Canny-Zernike Algorithm for Micro-Size Detection of Electronic Connectors." Traitement du Signal 39, no. 3 (2022): 899–906. http://dx.doi.org/10.18280/ts.390315.

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To detect the micro-size injection molded parts of electronic connectors, this paper establishes a complete size detection system based on machine vision, and measures the size through image acquisition and processing, according to the features of the injection molded parts. The proposed system is called the improved BM3D-Canny-Zernike algorithm. Specifically, the traditional block matching and three-dimensional filtering (BM3D) image denoising algorithm was improved to optimize the peak signal-to-noise ratio (PSNR) and reduce the mean squared error (MSE). Then, the Canny algorithm was improve

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Kanchanatripop, Phusit, and Dafang Zhang. "Adaptive Image Edge Extraction Based on Discrete Algorithm and Classical Canny Operator." Symmetry 12, no. 11 (2020): 1749. http://dx.doi.org/10.3390/sym12111749.

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In order to improve the accuracy of image edge detection, this paper studies the adaptive image edge detection technology based on discrete algorithm and classical Canny operator. First, the traditional sub-pixel edge detection method is illustrated based on the related literature research. Then, Canny operator is used for detection, the edge model of the quadric curve is established using discrete data, and the adaptive image edge parameters are obtained using one-dimensional gray moment. Experimental results show that the accuracy of feature detection is 99%, which can be applied to the prac

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Dong, Li Hong, and Peng Bing Zhao. "Application of Improved Canny Edge Detection Algorithm in Coal-Rock Interface Recognition." Applied Mechanics and Materials 220-223 (November 2012): 1279–83. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.1279.

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The coal-rock interface recognition is one of the critical automated technologies in the fully mechanized mining face. The poor working conditions underground result in the seriously polluted edge information of the coal-rock interface, which affects the positioning precision of the shearer drum. The Gaussian filter parameters and the high-low thresholds are difficult to select in the traditional Canny algorithm, which causes the information loss of gradual edge and the phenomenon of false edge. Consequently, this paper presents an improved Canny edge detection algorithm, which adopts the adap

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Liu, Lisang, Fenqiang Liang, Jishi Zheng, Dongwei He, and Jing Huang. "Ship infrared image edge detection based on an improved adaptive Canny algorithm." International Journal of Distributed Sensor Networks 14, no. 3 (2018): 155014771876463. http://dx.doi.org/10.1177/1550147718764639.

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Influenced by light reflection and water fog interference, ship infrared images are mostly blurred and have low signal-to-noise ratio. In this paper, an improved adaptive Canny edge detection algorithm for infrared image of ship is proposed, which aims to solve the threshold of the traditional Canny cannot be adjusted automatically and the shortcomings of sensitivity to noise. The contrast limited adaptive histogram equalization algorithm is adopted to enhance the infrared image, the morphological filter replaces the Gauss filter to smooth the image, and the OTSU algorithm is utilized to adjus

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Liu, Xumin, Xiaojun Wang, and Zilong Duan. "Canny Edge Detection Based On Iterative Algorithm." International Journal of Security and Its Applications 8, no. 5 (2014): 41–60. http://dx.doi.org/10.14257/ijsia.2014.8.5.05.

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Deepak, Mathur *. Dr. Prabhat Mathur. "EDGE DETECTION TECHNIQUES IN IMAGE PROCESSING WITH ELABORATIVE APPROACH TOWARDS CANNY." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 6 (2016): 638–43. https://doi.org/10.5281/zenodo.55797.

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Edge is defined as the boundary pixels that connect two separate regions. Edges are local changes in the image intensity. Edges characterize boundaries and are therefore a problem of fundamental importance in image processing.. Edge detection plays a very important role in image processing The edges detected by algorithms are used by advanced computer vision,medical field,Brain Tumor detection,geologic formation extraction,biometrix and many more fields.In this article we are going to survey various edge detection techniques such as sobel, Prewitt, Robert,, Marr Hildrith and Canny operators.Al

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E., Gangadevi, and Dr Shoba Rani R. "A Canny Edge Detection Algorithm for Automatic Identification of Plant Diseases." NeuroQuantology 20, no. 5 (2022): 1043–51. http://dx.doi.org/10.14704/nq.2022.20.5.nq22247.

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Plant diseases are important to investigate because they cause loss of plant life and product. Various forms of losses can occur in the field, in storage, or at any point between sowing and harvesting. Direct monitory loss and material loss are caused by the diseases. Plant diseases continue to cause agony to untold millions of people around the world, resulting in an estimated annual yield loss of 14% and a global economic loss of $220 billion dollars. Plants were afflicted by several diseases 250 million years ago, according to fossil evidence. The Plant sickness has been linked to a number

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Lang, Bai He, Ling Yun Shen, Tai Lin Han, and Yu Qun Chen. "An Adaptive Edge Detection Method Based on Canny Operator." Advanced Materials Research 255-260 (May 2011): 2037–41. http://dx.doi.org/10.4028/www.scientific.net/amr.255-260.2037.

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This paper proposes an adaptive Canny operator edge detection algorithm. The proposed method can automatically set the threshold value according to the different image gray-scale gradient histogram adaptively and improve the performance in the detail edge detection and good localization. Experiments show that this method produces better edge detection results performance than the Otsu method. Besides our method, Roberts operator, Prewitt operator, Sobel operator, Log operator and Canny operator based on Otsu algorithm are also tested for comparisons.

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