Relevant bibliographies by topics / Hough algorithm

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

Academic literature on the topic 'Hough algorithm'

Author: Grafiati
Published: 5 June 2025
Last updated: 8 July 2025

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Journal articles on the topic "Hough algorithm"

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Ketcham, Mahasak, and Thittaporn Ganokratanaa. "The analysis of lane detection algorithms using histogram shapes and Hough transform." International Journal of Intelligent Computing and Cybernetics 8, no. 3 (2015): 262–78. http://dx.doi.org/10.1108/ijicc-05-2014-0024.

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Purpose – The purpose of this paper is to develop a lane detection analysis algorithm by Hough transform and histogram shapes, which can effectively detect the lane markers in various lane road conditions, in driving system for drivers. Design/methodology/approach – Step 1: receiving image: the developed system is able to acquire images from video files. Step 2: splitting image: the system analyzes the splitting process of video file. Step 3: cropping image: specifying the area of interest using crop tool. Step 4: image enhancement: the system conducts the frame to convert RGB color image into grayscale image. Step 5: converting grayscale image to binary image. Step 6: segmenting and removing objects: using the opening morphological operations. Step 7: defining the analyzed area within the image using the Hough transform. Step 8: computing Houghline transform: the system operates the defined segment to analyze the Houghline transform. Findings – This paper presents the useful solution for lane detection by analyzing histogram shapes and Hough transform algorithms through digital image processing. The method has tested on video sequences filmed by using a webcam camera to record the road as a video file in a form of avi. The experimental results show the combination of two algorithms to compare the similarities and differences between histogram and Hough transform algorithm for better lane detection results. The performance of the Hough transform is better than the histogram shapes. Originality/value – This paper proposed two algorithms by comparing the similarities and differences between histogram shapes and Hough transform algorithm. The concept of this paper is to analyze between algorithms, provide a process of lane detection and search for the algorithm that has the better lane detection results.
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Zhao, Changfu, Hongchang Ding, Guohua Cao, and Ying Zhang. "A New Method for Detecting Compensation Hole Parameters of Automobile Brake Master Cylinder Based on Machine Vision." Journal of Advanced Transportation 2021 (April 8, 2021): 1–14. http://dx.doi.org/10.1155/2021/8864679.

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The machining accuracy of the compensation hole of the automobile brake master cylinder directly determines the safety of the automobile and the reliability of parking. How to detect the parameters of the compensation hole with high precision becomes a crucial issue. In this paper, by analyzing the principle of Hough transform detection technology and several optimization algorithms, a new method combining Zernike moment and improved gradient Hough transform is proposed to detect the circular hole parameters. The simulation experiment shows that the proposed algorithm satisfies 0.1 pixels in the coordinate detection of the center position, and the radius detection accuracy is 0.05 pixels, with fast detection speed and good robustness. Compared with the random Hough transform algorithm and the gradient Hough transform algorithm, the algorithm proposed in this paper has higher detection accuracy, faster detection speed, and better robustness, which meets the online detection accuracy requirements of the brake master cylinder compensation hole.
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WANG, QIANG, HONGBO CHEN, XIAORONG XU, and HAIYAN LIU. "A NEWLY MODIFIED ALGORITHM OF HOUGH TRANSFORM FOR LINE DETECTION." International Journal of Image and Graphics 05, no. 04 (2005): 715–27. http://dx.doi.org/10.1142/s0219467805001975.

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The heavy burden of computational complexity and massive storage requirement is the drawback of the standard Hough transform (SHT). To overcome the weakness of SHT, many modified approaches, for example, the probabilistic Hough transform (PHT), have been presented. However, a very important fact, which is that a line has its own width in a real digital image and the width of the line is uniform, was ignored by all of these modified algorithms of Hough transform. This phenomenon influenced the result of line detection. In this paper a new modified algorithm of Hough transform for line detection is proposed. In our algorithm, the fact mentioned above is fully considered and a strip-shaped area corresponding to the accumulate cells of HT is proposed. Experimental results have shown that our approach is efficient and promising, and the effect of detection is far better than the popular modified approaches.
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Faruq, Md Omar, Md Almash Alam, and Md Muktar Hossain. "A Comparisonal Study on Circle Detection for Real-World Images." Bangladesh Journal of Multidisciplinary Scientific Research 1, no. 2 (2019): 19–25. http://dx.doi.org/10.46281/bjmsr.v1i2.364.

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Real-life objects have different characteristics such as form characteristics, texture characteristics, and color characteristics and so on. The circular objects are the most common shape in our day to day lives and industrial production. So circle detection algorithm is ever ending research today. The most common algorithm is Circular Hough Transform which is used to detect a circle in an image. It is not very robust to noise so a simple approach to modified Circular Hough Transform algorithm is applied to detect the circle from an image. The image is pre-processed by edge detection. A comparison between Circular Hough Transform and modified Circular Hough Transform algorithm is presented in this research.
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Thazhuthaveetil, Matthew J., and Anish V. Shah. "Parallel hough transform algorithm performance." Image and Vision Computing 9, no. 2 (1991): 88–92. http://dx.doi.org/10.1016/0262-8856(91)90017-j.

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Smereka, Marcin, and Ignacy Dulęba. "Circular Object Detection Using a Modified Hough Transform." International Journal of Applied Mathematics and Computer Science 18, no. 1 (2008): 85–91. http://dx.doi.org/10.2478/v10006-008-0008-9.

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Circular Object Detection Using a Modified Hough TransformA practical modification of the Hough transform is proposed that improves the detection of low-contrast circular objects. The original circular Hough transform and its numerous modifications are discussed and compared in order to improve both the efficiency and computational complexity of the algorithm. Medical images are selected to verify the algorithm. In particular, the algorithm is applied to localize cell nuclei of cytological smears visualized using a phase contrast microscope.
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Zhou, Mingkuan, Weiwei Wang, Shenqing Shi, Zhen Huang, and Tao Wang. "Research on Global Navigation Operations for Rotary Burying of Stubbles Based on Machine Vision." Agriculture 15, no. 1 (2025): 114. https://doi.org/10.3390/agriculture15010114.

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In order to plan suitable navigation operation paths for the characteristics of rice fields in the middle and lower reaches of the Yangtze River and the operational requirements of straw rotary burying, this paper proposes a combination of the Hough matrix and RANSAC algorithms to extract the starting routes of straw boundaries; the algorithm adopts the Hough matrix to extract the characteristic points of the straw boundaries and remove the redundancies, and then reduces the influence of noise points caused by different straw shapes using the RANSAC algorithm to improve the accuracy of the starting route extraction. The algorithm extracts the starting routes of straw boundaries and the characteristic points of the straw boundaries and removes the redundancies, so as to improve the accuracy of the starting route extraction. The extraction test shows that under different scenes, the recognition accuracy of the path extraction method combining the Hough matrix and RANSAC algorithm is above 90%, and the algorithm takes no more than 0.51 s. Finally, the road test shows that the method meets the characteristics of tractor operation with a large turning radius and without reversing and satisfies the unmanned operation requirements of straw rotary burying in the field.
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CHANG, KUAN-TSUNG, and TIAN-YUAN SHIH. "LINEAR FEATURES EXTRACTION WITH AN ORIENTATION CONSTRAINED PROBABILISTIC HOUGH TRANSFORM." International Journal of Image and Graphics 08, no. 01 (2008): 157–68. http://dx.doi.org/10.1142/s0219467808003027.

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This study proposed a Hough Transform algorithm based on the probabilistic scheme termed as the Orientation Constrained Probabilistic Hough Transform. The orientation constraints for segmentation are applied to form compact and reliable sampling subsets. This process is subsequently followed by constrained searching. Numerical experiments are performed with both synthetic and real datasets indicate that the proposed method performs better than other algorithms in terms of correctness and omission rate. Moreover, computational time deemed necessary is much less than that for other algorithms.
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Ren, Long, Jia Wen Liao, Jian Zhong Cao, Hua Wang, Xiao Dong Zhao, and Han Meng. "An Improved Hough Transform Algorithm Based on Pyramid Method." Applied Mechanics and Materials 543-547 (March 2014): 1917–21. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.1917.

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Hough Transform[has become a common method in the usage of line detection because of its robustness. It is important in computer vision and image analysis. Usually, the standard Hough transform method (SHT) transform the points in image space into parameter space and vote for all the possible patterns passing through that point. But, there are two serious problems in the standard method of line detection. The first is the high computation complexity and the second is the large storage requirements .In order to solve the two problems, this paper raise a fast-Hough transform algorithm base on pyramid algorithm. First of all we need to desample the primitive binary image with n times; and execute the Hough transform in the nth level image to get the parameter of straight line in this image, which is used in the n-1 level image. Finally we can get the parameter of lines in the primitive image. Experiments show that this method can extremely reduces the computational time.
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Li, Qiang, and Qi Yuan Sun. "Research on Matching Pair Purification Methods of Image Based on SIFT Algorithm." Applied Mechanics and Materials 713-715 (January 2015): 1851–54. http://dx.doi.org/10.4028/www.scientific.net/amm.713-715.1851.

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In view of the SIFT algorithm in image matching will produce a lot of mismatches, the paper has applied a method which is based on Hough Transform will remove the SIFT matching error effectively. Firstly, to use the SIFT algorithm finish the image matching roughly. And then, using the Hough Transform to form the equal division hough units. And according to the matching parameter to distribute all the match into the hough units. The match in the units which has least matching-pair will be deleted. Experimental results show that the method can effectively improve the matching accuracy of feature matching and it lays a foundation for the following robot vision navigation.
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Dissertations / Theses on the topic "Hough algorithm"

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Li, Duwang. "Invariant pattern recognition algorithm using the Hough Transform." PDXScholar, 1989. https://pdxscholar.library.pdx.edu/open_access_etds/3899.

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A new algorithm is proposed which uses the Hough Transform to recognize two dimensional objects independent of their orientations, sizes and locations. The binary image of an object is represented by a set of straight lines. Features of the straight lines, namely the lengths and the angles of their normals, their lengths and the end point positions are extracted using the Hough Transform. A data structure for the extracted lines is constructed so that it is efficient to match the features of the lines of one object to those of another object, and determine if one object is a rotated and/or scaled version of the other. Finally a generalized Hough Transform is used to match the end points of the two sets of lines. The simulation experiments show good results for objects with significant linear features .
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Sparrow, Patricia B. "Implementation and testing of Hough algorithm for line detection in image processing." DigitalCommons@Robert W. Woodruff Library, Atlanta University Center, 1985. http://digitalcommons.auctr.edu/dissertations/2411.

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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 poteaux est appelé l’algorithme YuRHoS. Le SEES développé comme système de support d'aide à la mobilité VIP a été intégré avec succès à plusieurs dispositifs tels que le serveur distant dénommé iSEE, le serveur local embarqué dénommé SEE-phone et la canne intelligente dénommée SEE-stick. Les performances de SEE-stick ont été améliorées grâce à l'algorithme YuRHoS qui permet de discriminer avec précision les objets (obstacles) en forme de poteau parmi les objets détectés. La comparaison des résultats de détection des poteaux avec ceux des autres algorithmes a conclu que l'algorithme YuRHoS était plus efficace et précis. Le lieu et la couleur des poteaux de test d’évaluation étaient deux des facteurs les plus importants qui influaient sur la capacité du SEE-stick à détecter leur présence. Le niveau de précision de SEE-stick est optimal lorsque le test d’évaluation est effectué à l'extérieur et que les poteaux sont de couleur argentée. Les statistiques montrent que la performance de l'algorithme YuRHoS à l'intérieur était 0,085 fois moins bonne qu'à l'extérieur. De plus, la détection de la présence de poteaux de couleur argentée est 11 fois meilleure que celle de poteaux de couleur noir<br>This research aimed to develop a technology system of mobility aid for Visually Impaired Person (VIP) called Smart Environment Explorer Stick (SEES).Particular purpose of this research was developing new algorithm in improving accuracy of SEE-stick for pole detection using distance calculation method and vertical line pair search based on Canny edge detection optimization and Hough transform. Henceforth, the pole detection algorithm was named as YuRHoS algorithm.The developed SEES as supporting system of VIP mobility aid had been successfully integrated several devices such as global remote server (iSEE), embedded local server (SEE-phone) and smart stick (SEE-stick). Performance of SEE-stick could be improved through YuRHoS algorithm, which was able to fix the accuracy of SEE-stick in detecting pole. Test comparison of pole detection results among others algorithm concluded that YuRHoS algorithm had better accuracy in pole detection.Two most significant factors affecting SEE-stick ability in detecting pole was test location and pole color. Level of accuracy of SEE-stick would be optimum once the test location was performed outdoor and pole color was silver. Statistics result shown that YuRHoS algorithm performance indoor was 0.085 times worse than outdoor. Meanwhile, silver-pole-color as object detection could increase YuRHoS algorithm performance as much as 11 times better compare to black-pole-color
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Levrini, Giacomo. "Feasibility study and emulation of the Hough Transform algorithm on FPGA devices for ATLAS Phase-II trigger upgrade." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/22105/.

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In the next 10 years, a radical upgrade is expected for the Large Hadron Collider focused in achieving the highest values in the instantaneous and integrated luminosity. Both the subdetectrors of the experiments and their data acquisition systems will need an upgrade. For the Phase-II upgrade of the Trigger and Data Acquisition System (TDAQ) of the ATLAS experiment a common platform has been created to share the common firmware, software and tools that are ongoing and that will come in the next years within the ATLAS TDAQ collaboration. The environment includes a set of design procedures, a virtual machine as repository for the firmware and some automatic tools for the continuous integration and versioning. The platform is under testing, as the firmware will be tested on the TDAQ upgraded, it will also be used for the prototype cards that will be produced as demonstrator for the ATLAS Hardware Tracking for the Trigger (HTT) system. For the HTT project a physical environment is being prepared, exploiting Peripheral Component Interconnect express (PCIe) and ACTA crates. My personal work has been the design of a part of track-fitting algorithms, in particular the one using the Hough Transform. This implementation has been required by the ATLAS experiment as an alternative solution to the baseline proposal accepted and described in the TDAQ Upgrade Technical Design Report (TDR). I have developed and tested a set of pattern vectors used not only in the simulation and validation of the algorithm, but also in the hadware integration on a FPGA based hardware accelerator. The used technology is based on high-performance Xilinx Ultrascale+ FPGA, implemented on VCU1525 board. This work is going to be validated by the ATLAS collaboration very soon, so to understand how we can proceed in the future upgrade. Bologna is the only Italian institute which participates in the integration of a tracking algorithm in the ATLAS trigger upgrade, using high performance FPGA-based hardware.
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Santarelli, Alice. "FPGA-based hardware demonstrator of a Hough transform pattern recognition algorithm for the ATLAS Phase-II trigger upgrade." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amslaurea.unibo.it/25599/.

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This Master Thesis discusses the Phase-II upgrade of the Trigger and Data Acquisition system of the detector called A Toroidal LHC ApparatuS (ATLAS). An R&D program, which has included the creation of two task forces, was launched in the 2021 Spring with the aim to produce one engineered solution for the track reconstruction at the Event Filter (EF) level. The Electronic group of the University of Bologna is taking part in the proposal of the heterogeneous commodity task force, which consists of the previous project called Hardware Tracking for the Trigger. The heterogeneous solution is based on a mixed commodity platform of classic processors and accelerators, where track reconstruction is expected to be performed via the use of mathematical functions, for example through the implementation of Hough Transform algorithm on the FPGA which will be part of the EF of ATLAS Phase-II. The R&D activities performed until now include the development of the firmware for the HT. Final goal of this Master Thesis is the creation of a hardware demonstrator able to test the ongoing firmware design. To fulfill this purpose, a new firmware architecture is exploited and it relies on a manageable Peripheral Component Interconnect Express transmission. The integration of the two firmware designs is realized with the development of a two first-in-first-out structure. In this way it is demonstrated the correct implementation of the ongoing Hough Transform firmware design.
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Santamaria, Clémentine. "Quest for new nuclear magic numbers with MINOS." Thesis, Paris 11, 2015. http://www.theses.fr/2015PA112153/document.

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Le détecteur MINOS a été développé jusqu'à mi-2013 pour la spectroscopie γ prompte de noyaux très exotiques à partir de réactions d’arrachage de protons. Il est composé d'une cible épaisse d'hydrogène liquide pour augmenter la luminosité et d’une chambre à projection temporelle (TPC) pour reconstruire la position du vertex de réaction et de compenser l'effet de la cible épaisse sur la correction Doppler.La chambre à projection temporelle a été développée avec l'expertise du CEA-Irfu sur les détecteurs gazeux de type Micromegas. Dans un premier temps, différentes solutions pour la TPC ont été testées dans une chambre d'essai avec une source α et des mesures de rayons cosmiques. Des muons cosmiques ont été détectés pour la première fois en utilisant la chambre d'essai en début 2013 et ont validé l'utilisation d'un plan de détection Micromegas. Le premier prototype de TPC a été achevé en mai 2013 et nous avons utilisé un banc de rayons cosmiques pour estimer l’efficacité de la TPC.MINOS a ensuite été expédié au Japon et un test de performance sous faisceau a été réalisée à l'installation médicale HIMAC (Chiba, Japon) avec deux cibles minces au lieu de la cible épaisse d'hydrogène pour valider l'algorithme de reconstruction et la résolution de la position du vertex. Un algorithme de reconstruction de traces basé sur la transformée de Hough a été mis au point pour l'analyse des données, testé avec ces données, et comparé à des simulations.La première campagne de physique avec MINOS a eu lieu en mai 2014, avec SEASTAR. Elle s’est concentrée sur la première spectroscopie des ⁶ ⁶ Cr, ⁷⁰,⁷²Fe et ⁷⁸Ni. L'analyse de la spectroscopie du ⁶ ⁶Cr a révélé deux transitions, assignées aux deux premiers états excités. Une interprétation avec des calculs de modèle en couches montre que le maximum de collectivité quadripolaire se produit à N = 40 le long de la chaîne isotopique de chrome.Le ⁶ ⁶Cr est toujours placé dans la région de l’Îlot d’Inversion à N = 40 et les calculs de modèle en couches ainsi que la comparaison avec des calculs basés sur HFB suggèrent une extension de cet Îlot d’Inversion vers N = 50 en dessous du ⁷⁸Ni. L'analyse des ⁷⁰,⁷²Fe effectuée par C. Louchart (TU Darmstadt, Allemagne) révèle la même tendance que pour les isotopes de chrome. Les données et notre interprétation par le modèle en couches suggère une grande collectivité les Cr et Fe riches en neutrons, éventuellement jusqu'à N = 50, ce qui remettrait en cause la solidité de la fermeture de couche N = 50 en dessous du ⁷⁸Ni<br>The MINOS device has been developed until mid-2013 for in-beam γ spectroscopy of very exotic nuclei from proton knockout reactions. It is composed of a thick liquid hydrogen target to achieve higher luminosities and a Time Projection Chamber (TPC) to reconstruct the vertex position and compensate for the thick target effect on the Doppler correction.The Time Projection Chamber has been developed with the expertise of CEA-IRFU in gas detectors and Micromegas detectors. At first, different solutions for the TPC were tested in a test chamber with an α source and cosmic-ray measurements. Cosmic rays were detected for the first time using the test chamber in early 2013 and validated the use of a Micromegas detection plane. The first TPC prototype was finished in May 2013, and we used a cosmic-ray bench to estimate the effiiciency of the TPC. The MINOS device was then shipped to Japan and an in-beam performance test was performed at the HIMAC medical facility (Chiba, Japan) with two thin targets instead of the thick hydrogen target to validate the tracking algorithm and the vertex position resolution. A tracking algorithm for the offline analysis based on the Hough transform has been developed, tested with the data, and compared with simulations.The first physics campaign using MINOS took place in May 2014 with SEASTAR. It focused on the first spectroscopy of ⁶ ⁶ Cr, ⁷⁰,⁷²Fe, and ⁷⁸Ni. The analysis of the ⁶⁶Cr spectroscopy revealed two transitions, assigned to the two first excited states. An interpretation with shell model calculations shows that the maximum of quadrupole collectivity occurs at N=40 along the Cr isotopic chain.⁶⁶Cr is still placed in the Island of Inversion region of N=40 and the shell model calculations as well as comparison with HFB-based calculations suggest an extension of this Island of Inversion towards N=50 below ⁷⁸Ni. The analysis of ⁷⁰,⁷²Fe performed by C. Louchart (TU Darmstadt, Germany) reveals the same trend as for Cr isotopes, with a maximum of deformation at N=42. The full data set and our shell-model interpretation suggests a large collectivity for neutron-rich Cr and Fe, possibly up to N=50, questioning the robustness of the N=50 shell closure below ⁷⁸Ni
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Rodriguez, Artolazabal Jose Antonio. "Exploiting invariance in Hough transform algorithms." Thesis, University of Surrey, 2007. http://epubs.surrey.ac.uk/972/.

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Hříbek, Petr. "Detekce elipsy v obraze." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2008. http://www.nusl.cz/ntk/nusl-235427.

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The thesis introduces methods used for an ellipse detection. Each method is theoretically described in current subsection. The description includes methods like Hough transform, Random Hough transform, RANSAC, Genetic Algorithm and improvements with optimalization. Further there are described modifications of current procedures in the thesis to reach better results. Next to the last chapter represents testing parameters of speed, quality and accuracy of implemented algorithms. There is a conclusion of testing and a result discussion at the end.
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Ku, Kuo-Lung. "Algorithms and architectures for the Hough transformation /." Thesis, Connect to this title online; UW restricted, 1987. http://hdl.handle.net/1773/5909.

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Duba, Nikolas. "Jednoduché rozpoznávání písma." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-236979.

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This thesis is focused on optical character recognition and its processing. The goal of this application is to make it possible easily track daily expenses. It can be used by an individual or by a company as a monitoring tool. The main principle is to make this tool most as user friendly as it can be. The application gets its input from hardware, such as a scanner or camera, and analyzes the content of the cash voucher for further processing. To analyze the voucher, the application employs different optical character recognition methods. The result is subsequently parsed. Detailed explanations of used methods are inside the document. The application output is a filled database with cash voucher details. Another part of the work is an information system with the main purpose of displaying the collected data.
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Book chapters on the topic "Hough algorithm"

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Tu, Chunling, Barend Jacobus van Wyk, Karim Djouani, Yskandar Hamam, and Shengzhi Du. "A Super Resolution Algorithm to Improve the Hough Transform." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21593-3_9.

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Shin, Hyeoncheol, and Kwangil Lee. "High-Speed Horizon Line Detection Algorithm Using Dual Hough Algorithm for Marine Image." In Advances in Computer Science and Ubiquitous Computing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9341-9_83.

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van den Braak, Gert-Jan, Cedric Nugteren, Bart Mesman, and Henk Corporaal. "Fast Hough Transform on GPUs: Exploration of Algorithm Trade-Offs." In Advanced Concepts for Intelligent Vision Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23687-7_55.

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To, Cuong, Tien Thanh Nguyen, and Alan Wee-Chung Liew. "A Hough Transform-Based Biclustering Algorithm for Gene Expression Data." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45652-1_11.

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Zhang, Baoju, and Jingqi Fei. "An Iris Location Algorithm Based on Gray Projection and Hough Transform." In Lecture Notes in Electrical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6504-1_157.

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Syed, Mohammad Haider, and Santosh Kumar. "Road Lane Line Detection Based on ROI Using Hough Transform Algorithm." In Proceedings of Third International Conference on Computing, Communications, and Cyber-Security. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1142-2_45.

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Cheng, Siming, Kangling Fang, and Xinhai Liu. "Separating Algorithm for Quasi-Circle Overlapping Images Based on Improved Hough Transform." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34531-9_40.

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Chattopadhyay, Asis Kumar, Tanuka Chattyopadhyay, Tuli De, and Saptarshi Mondal. "Independent Component Analysis for Dimension Reduction Classification: Hough Transform and CASH Algorithm." In Astrostatistical Challenges for the New Astronomy. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3508-2_9.

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Xu, Di-jian, Xing-hua Liu, and Jing-rui Wang. "An Algorithm of Iris Location Based on Gray Projection and Improved Hough Transform." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03664-4_29.

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Kazhagamani, Usha, and Ezhilarasan Murugasen. "A Hough Transform Based Feature Extraction Algorithm for Finger Knuckle Biometric Recognition System." In Smart Innovation, Systems and Technologies. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07353-8_54.

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Conference papers on the topic "Hough algorithm"

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Qin, Lijuan, Shiyi Wang, and Xiong Xu. "HSV-enhanced Canny-Hough algorithm for robust lane line recognition." In International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2024), edited by Liang Hu. SPIE, 2025. https://doi.org/10.1117/12.3064448.

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Chen, Zhenqi, Shaopeng Pang, Mingjun Du, Fangzhou Xu, and Peng Ji. "Center Positioning Method for Fresnel Lens Based on Canny-Hough Detection Algorithm." In 2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS). IEEE, 2024. http://dx.doi.org/10.1109/ddcls61622.2024.10606672.

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Kazimirov, Danil, Dmitry Nikolaev, Ekaterina Rybakova, and Arseniy Terekhin. "Generalization of Brady-Yong algorithm for fast Hough transform to arbitrary image size." In 2024 The 5th Symposium on Pattern Recognition and Applications, edited by Xiaodan Pang. SPIE, 2025. https://doi.org/10.1117/12.3056638.

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Li, Hanxi, Hong Zheng, and Yang Wang. "Segment Hough Transform -- a Novel Hough-based Algorithm for Curve Detection." In Fourth International Conference on Image and Graphics (ICIG 2007). IEEE, 2007. http://dx.doi.org/10.1109/icig.2007.114.

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McLauchlan, Philip, and John Mayhew. "Needles: A Stereo Algorithm for Texture." In Image Understanding and Machine Vision. Optica Publishing Group, 1989. http://dx.doi.org/10.1364/iumv.1989.tud1.

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Abstract:
This paper describes Needles, an edge based stereo algorithm designed to take advantage of the smoothness of many textured surfaces. The correspondence problem is not addressed explicitly. Rather, a simple two stage process extracts surface position and orientation directly. Firstly local disparity histograms over a large range are constructed. Maxima in the histograms correspond to the possible surface depths. A Hough transform is used to fit a plane to the ambiguous disparity points close to the histogram maxima. This confirms and makes more precise the estimates of disparity obtained from the histograms. Local surface disparity and orientation are calculated from the best planar fit after all the histogram maxima (above a threshold) have been tried. This is an extension of an algorithm described in (Pollard 1985) which uses a Hough transform to find local surface orientation without explicit matching. In his algorithm pairs of possible matches vote for the disparity gradient between them. When all pairs have voted the winning disparity gradient (and hence, surface orientation) has the highest Hough accumulator value.
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Zheng, Yunping, Ruijun Li, Wenjie Huang, and Mudar Sarem. "A New NAM-based Hough Transform Algorithm." In 2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). IEEE, 2018. http://dx.doi.org/10.1109/fskd.2018.8687179.

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Jiankui, Zeng, and Xiang Lijuan. "Fast Hough transform algorithm for radar detection." In 2010 2nd International Conference on Industrial Mechatronics and Automation (ICIMA 2010). IEEE, 2010. http://dx.doi.org/10.1109/icindma.2010.5538334.

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Zeng jiankui and Yuan Shanzun. "Improved Hough transform algorithm for radar detection." In 2009 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS). IEEE, 2009. http://dx.doi.org/10.1109/peits.2009.5406778.

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Delprado, Anton, and Ray Eaton. "An efficient single Vote Hough tracking algorithm." In 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV 2012). IEEE, 2012. http://dx.doi.org/10.1109/icarcv.2012.6485398.

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Xu, Yanfeng, Wenbin Li, Feng Kang, and Yuesheng Tan. "Fast line detection algorithm based on Hough transform." In International Conference of Information Science and Management Engineering. WIT Press, 2014. http://dx.doi.org/10.2495/isme20140351.

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Reports on the topic "Hough algorithm"

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Li, Duwang. Invariant pattern recognition algorithm using the Hough Transform. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.5783.

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