Relevant bibliographies by topics / Canny edge detection algorithm

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Canny edge detection algorithm'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Canny edge detection algorithm"

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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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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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Dissertations / Theses on the topic "Canny edge detection algorithm"

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Zavistanavičiūtė, Rasa. "Object detection algorithms analysis and implementation for augmented reality system." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2013. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2012~D_20131105_093556-36296.

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Object detection is the initial step in any image analysis procedure and is essential for the performance of object recognition and augmented reality systems. Research concerning the detection of edges and blobs is particularly rich and many algorithms or methods have been proposed in the literature. This master‟s thesis presents 4 most common blob and edge detectors, proposes method for detected numbers separation and describes the experimental setup and results of object detection and detected numbers separation performance. Finally, we determine which detector demonstrates the best results
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Yusro, Muhammad. "Development of new algorithm for improving accuracy of pole detection to the supporting system of mobility aid for visually impaired person." Thesis, Université Clermont Auvergne‎ (2017-2020), 2017. http://www.theses.fr/2017CLFAC107/document.

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Ces travaux de recherche visaient à développer un système d'aide à la mobilité pour les personnes ayant une déficience visuelle (VIP ‘Visually Impaired Person’) appelé ‘Smart Environment Explorer Stick (SEES)’. Le but particulier de cette recherche était de développer de nouveaux algorithmes pour améliorer la précision de la détection de la présence de poteaux de la canne SEE-stick en utilisant la méthode de calcul de distance et la recherche de paires de lignes verticales basées sur l'optimisation de la technique de détection de contour de Canny. Désormais, l'algorithme de détection des potea
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Vannucci, Maria Chiara. "Algoritmi di segmentazione di immagini mediche." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10878/.

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Nell'ambito dell'elaborazione delle immagini, si definisce segmentazione il processo atto a scomporre un'immagine nelle sue regioni costituenti o negli oggetti che la compongono. Ciò avviene sulla base di determinati criteri di appartenenza dei pixel ad una regione. Si tratta di uno degli obiettivi più difficili da perseguire, anche perché l'accuratezza del risultato dipende dal tipo di informazione che si vuole ricavare dall'immagine. Questa tesi analizza, sperimenta e raffronta alcune tecniche di elaborazione e segmentazione applicate ad immagini digitali di tipo medico. In particolare l'
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Vápeník, Radovan. "Automatická optická inspekce." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-217913.

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This work deals with the technical possibilities for automated optical inspection and the arrangements for monitoring the implementation of established elements. There are used methods of detection elements, including advanced algorithm processing. With the described methods was created program and each method was tested. The aim was on the clear description of the problem, the optimal design and processing program with objective results with the lowest number of false detection.
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Nalavolu, Praveen Reddy. "PERFORMANCE ANALYSIS OF SRCP IMAGE BASED SOUND SOURCE DETECTION ALGORITHMS." UKnowledge, 2010. http://uknowledge.uky.edu/gradschool_theses/50.

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Steered Response Power based algorithms are widely used for finding sound source location using microphone array systems. SRCP-PHAT is one such algorithm that has a robust performance under noisy and reverberant conditions. The algorithm creates a likelihood function over the field of view. This thesis employs image processing methods on SRCP-PHAT images, to exploit the difference in power levels and pixel patterns to discriminate between sound source and background pixels. Hough Transform based ellipse detection is used to identify the sound source locations by finding the centers of elliptic
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Larsson, Mathias. "Machine vision for finding a joint to guide a welding robot." Thesis, University West, Department of Engineering Science, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-1783.

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<p>This report contains a description on how it is possible to guide a robot along an edge, by using a camera mounted on the robot. If stereo matching is used to calculate 3Dcoordinates of an object or an edge, it requires two images from different known positions and orientations to calculate where it is. In the image analysis in this project, the Canny edge filter has been used. The result from the filter is not useful directly, because it finds too many edges and it misses some pixels. The Canny edge result must be sorted and finally filled up before the final calculations can be started. T
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Guler, Muhammet Ali. "Detection Of Earthquake Damaged Buildings From Post-event Photographs Using Perceptual Grouping." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12604982/index.pdf.

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Two approaches were developed for detecting earthquake damaged buildings from post-event aerial photographs using shadow analysis and perceptual grouping. In the first approach, it is assumed that the vector boundaries of the buildings are not known a priori. Therefore, only the post-event aerial photographs were used to detect the collapsed buildings. The approach relies on an idea that if a building is fully damaged then, it will not generate a closed contour. First, a median filter is applied to remove the noise. Then, the edge pixels are detected through a Canny edge detector and the line
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Bilen, Burak. "Model Based Building Extraction From High Resolution Aerial Images." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12604984/index.pdf.

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A method for detecting the buildings from high resolution aerial images is proposed. The aim is to extract the buildings from high resolution aerial images using the Hough transform and the model based perceptual grouping techniques.The edges detected from the image are the basic structures used in the building detection procedure. The method proposed in this thesis makes use of the basic image processing techniques. Noise removal and image sharpening techniques are used to enhance the input image. Then, the edges are extracted from the image using the Canny edge detection algorithm. The edges
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Guducu, Hasan Volkan. "Building Detection From Satellite Images Using Shadow And Color Information." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609920/index.pdf.

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A method for detecting buildings from satellite/aerial images is proposed in this study. The aim is to extract rectilinear buildings by using hypothesize first verify next manner. Hypothesis generation is accomplished by using edge detection and line generation stages. Hypothesis verification is carried out by using information obtained both from the color segmentation of HSV representation of the image and the shadow detection stages&rsquo<br>output. Satellite/aerial image is firstly filtered to sharpen the edges. Then, edges are extracted using Canny edge detection algorithm. These edges are
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Němec, Zbyšek. "Derichův detektor hran." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-235475.

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This thesis presents the Deriche edge detector as an interesting alternative to the commonly used edge detectors. The Deriche edge detector's design is presented to the reader as well as its strengths and weaknesses. Performance issues of the Deriche edge detector are described in comparison with the Canny edge detector together with recommendations for using the Deriche detector. Finally, edge detection quality of the Deriche edge detector is compared to the Canny edge detector using robust subjective evaluation method.
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Book chapters on the topic "Canny edge detection algorithm"

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Mokrzycki, Wojciech, and Marek Samko. "Canny Edge Detection Algorithm Modification." In Computer Vision and Graphics. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33564-8_64.

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Cheng, You-e. "An improved Canny Edge Detection Algorithm." In Recent Advances in Computer Science and Information Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25766-7_73.

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Mishra, Satyam, and Le Trung Thanh. "SATMeas - Object Detection and Measurement: Canny Edge Detection Algorithm." In Artificial Intelligence and Mobile Services – AIMS 2022. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-23504-7_7.

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Murali, Gunji Bala, V. Santosh Kumar, Dibya Narayan Behera, Kapil Kumar Mohanta, Omkar Tulankar, and Sanketh S. Salimath. "Pothole Detection on Roads Using Canny Edge Detection Algorithm." In Applications of Computational Methods in Manufacturing and Product Design. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0296-3_60.

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Ojashwini, R. N., R. Gangadhar Reddy, R. N. Rani, and B. Pruthvija. "Edge Detection Canny Algorithm Using Adaptive Threshold Technique." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5679-1_45.

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Li, Jun, and Sheng Ding. "A Research on Improved Canny Edge Detection Algorithm." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23223-7_13.

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Senthilkumar, K. K., E. Avantika, B. Gayathri, and Vaithiyanathan Dhandapani. "VLSI Implementation of Reconfigurable Canny Edge Detection Algorithm." In Big Data Analytics in Astronomy, Science, and Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-58502-9_7.

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Yang, Aolei, Weiwei Jiang, and Ling Chen. "An Adaptive Edge Detection Algorithm Based on Improved Canny." In Communications in Computer and Information Science. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6370-1_56.

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Chikmurge, Diptee, and Shilpa Harnale. "Feature Extraction of DICOM Images Using Canny Edge Detection Algorithm." In Advances in Intelligent Systems and Computing. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5520-1_18.

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Wang, Mingjie, Jesse S. Jin, Yifei Jing, Xianfeng Han, Lei Gao, and Liping Xiao. "The Improved Canny Edge Detection Algorithm Based on an Anisotropic and Genetic Algorithm." In Communications in Computer and Information Science. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2260-9_14.

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Conference papers on the topic "Canny edge detection algorithm"

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Zhang, Hongpeng, Chang Liu, Liangjie Feng, and Yang Yu. "Improved Canny Edge Detection Algorithm." In 2024 9th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS). IEEE, 2024. https://doi.org/10.1109/iciibms62405.2024.10792784.

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Wang, Desheng, Yawen Lin, Yue Sun, Min Zhang, Yulong Sun, and Weiguo Lin. "Cigarette strip defect detection based on Canny edge detection algorithm." In 4th International Conference on Image Processing and Intelligent Control (IPIC 2024), edited by Kelin Du and Azlan bin Mohd Zain. SPIE, 2024. http://dx.doi.org/10.1117/12.3038453.

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Gao, Yuan, and Fengyang Gao. "Optimize the Edge Detection Algorithm of Canny Operator Threshold Selection." In 2024 International Conference on Artificial Intelligence and Power Systems (AIPS). IEEE, 2024. http://dx.doi.org/10.1109/aips64124.2024.00063.

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Wu, Zilong, DongDong Xie, WeiQiang Sun, and Leijing Yang. "Optimization of Wafer Scan Image Based on Improved Canny Edge Detection." In 2024 2nd International Conference on Algorithm, Image Processing and Machine Vision (AIPMV). IEEE, 2024. http://dx.doi.org/10.1109/aipmv62663.2024.10692200.

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Tan, Tingfang, Lihui Wang, and Wenlong Zhou. "Edge Detection of Plant Root Images Based on Improved Canny Algorithm." In 2024 Photonics & Electromagnetics Research Symposium (PIERS). IEEE, 2024. http://dx.doi.org/10.1109/piers62282.2024.10618774.

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Selvakumar, P., and S. Hari Ganesh. "Expression of Concern for: Tamil Character Recognition Using Canny Edge Detection Algorithm." In 2017 World Congress on Computing and Communication Technologies (WCCCT). IEEE, 2017. http://dx.doi.org/10.1109/wccct40583.2017.10702674.

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Hashemi, Mahdi, Mohammed A. S. Khalid, and Roche Christopher. "SYCL-based Acceleration of Canny Edge Detector Algorithm Using DPC++." In 2024 IEEE 67th International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2024. http://dx.doi.org/10.1109/mwscas60917.2024.10658696.

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Zhang, Jing. "Edge Detection of Noise Images Based on Improved Canny Algorithm with Adaptive Threshold." In 2024 International Conference on Advances in Electrical Engineering and Computer Applications (AEECA). IEEE, 2024. https://doi.org/10.1109/aeeca62331.2024.00126.

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Wang, Bing, and ShaoSheng Fan. "An Improved CANNY Edge Detection Algorithm." In 2009 Second International Workshop on Computer Science and Engineering. IEEE, 2009. http://dx.doi.org/10.1109/wcse.2009.718.

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Rong, Weibin, Zhanjing Li, Wei Zhang, and Lining Sun. "An improved Canny edge detection algorithm." In 2014 IEEE International Conference on Mechatronics and Automation (ICMA). IEEE, 2014. http://dx.doi.org/10.1109/icma.2014.6885761.

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Reports on the topic "Canny edge detection algorithm"

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Clarke, J., and L. R. Wright. The uncertainty-aware canny operator edge detection method. National Physical Laboratory, 2023. http://dx.doi.org/10.47120/npl.ms49.

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Clausen, Jay, Vuong Truong, Sophia Bragdon, et al. Buried-object-detection improvements incorporating environmental phenomenology into signature physics. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45625.

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The ability to detect buried objects is critical for the Army. Therefore, this report summarizes the fourth year of an ongoing study to assess environ-mental phenomenological conditions affecting probability of detection and false alarm rates for buried-object detection using thermal infrared sensors. This study used several different approaches to identify the predominant environmental variables affecting object detection: (1) multilevel statistical modeling, (2) direct image analysis, (3) physics-based thermal modeling, and (4) application of machine learning (ML) techniques. In addition, th
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Trujillo, Christopher J. A thesis on the Development of an Automated SWIFT Edge Detection Algorithm. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1296634.

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Asari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan, and Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Pipeline Research Council International, Inc. (PRCI), 2015. http://dx.doi.org/10.55274/r0010891.

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A novel algorithmic framework for the robust detection and classification of machinery threats and other potentially harmful objects intruding onto a pipeline right-of-way (ROW) is designed from three perspectives: visibility improvement, context-based segmentation, and object recognition/classification. In the first part of the framework, an adaptive image enhancement algorithm is utilized to improve the visibility of aerial imagery to aid in threat detection. In this technique, a nonlinear transfer function is developed to enhance the processing of aerial imagery with extremely non-uniform l
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