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Journal articles on the topic 'Modified Hough Transform'

Author: Grafiati

Published: 4 June 2025

Last updated: 23 June 2025

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1

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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2

Berger, Alan D., and Pradeep K. Khosla. "The modified adaptive Hough transform (MAHT)." Journal of Robotic Systems 7, no. 2 (1990): 277–90. http://dx.doi.org/10.1002/rob.4620070209.

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3

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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4

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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Jiankui, Zeng, He Zishu, Mathini Sellathurai, and Liu Hongming. "Modified Hough Transform for Searching Radar Detection." IEEE Geoscience and Remote Sensing Letters 5, no. 4 (2008): 683–86. http://dx.doi.org/10.1109/lgrs.2008.2002574.

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6

Shen, Fei, and Han Wang. "Corner detection based on modified Hough transform." Pattern Recognition Letters 23, no. 8 (2002): 1039–49. http://dx.doi.org/10.1016/s0167-8655(02)00035-1.

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7

Aldoshkin, Dmitry N., and Roman Y. Tsarev. "Evaluation of Two-Dimensional Angular Orientation of a Mobile Robot by a Modified Algorithm Based on Hough Transform." Cybernetics and Information Technologies 18, no. 2 (2018): 112–22. http://dx.doi.org/10.2478/cait-2018-0032.

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Abstract This paper proposes an algorithm that assesses the angular orientation of a mobile robot with respect to its referential position or a map of the surrounding space. In the framework of the suggested method, the orientation problem is converted to evaluating a dimensional rotation of the object that is abstracted as a polygon (or a closed polygonal chain). The method is based on Hough transform, which transforms the measurement space to a parametric space (in this case, a two-dimensional space [θ, r] of straight-line parameters). The Hough transform preserves the angles between the straight lines during rotation, translation, and isotropic scaling transformations. The problem of rotation assessment then becomes a one-dimensional optimization problem. The suggested algorithm inherits the Hough method’s robustness to noise.

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8

Zhdanov, I. N., A. S. Potapov, and O. V. Shcherbakov. "Erythrometry method based on a modified Hough transform." Journal of Optical Technology 80, no. 3 (2013): 201. http://dx.doi.org/10.1364/jot.80.000201.

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9

Dobeš, M., J. Martinek, D. Skoupil, Z. Dobešová, and J. Pospíšil. "Human eye localization using the modified Hough transform." Optik 117, no. 10 (2006): 468–73. http://dx.doi.org/10.1016/j.ijleo.2005.11.008.

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10

TIPWAI, P., and S. MADARASMI. "A Modified Generalized Hough Transform for Image Search." IEICE Transactions on Information and Systems E90-D, no. 1 (2007): 165–72. http://dx.doi.org/10.1093/ietisy/e90-1.1.165.

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11

Katru, Amandeep, and Anil Kumar. "Improved Parallel Lane Detection Using Modified Additive Hough Transform." International Journal of Image, Graphics and Signal Processing 8, no. 11 (2016): 10–17. http://dx.doi.org/10.5815/ijigsp.2015.11.02.

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12

Katru, Amandeep, and Anil Kumar. "Improved Parallel Lane Detection Using Modified Additive Hough Transform." International Journal of Image, Graphics and Signal Processing 8, no. 11 (2016): 10–17. http://dx.doi.org/10.5815/ijigsp.2016.11.02.

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13

Ji Siwei and He Mingxing. "Comments on “Modified Hough Transform for Searching Radar Detection”." IEEE Geoscience and Remote Sensing Letters 6, no. 3 (2009): 616. http://dx.doi.org/10.1109/lgrs.2009.2019473.

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14

Yang, M. C. K., Jong-Sen Lee, Cheng-Chang Lien, and Chung-Lin Huang. "Hough transform modified by line connectivity and line thickness." IEEE Transactions on Pattern Analysis and Machine Intelligence 19, no. 8 (1997): 905–10. http://dx.doi.org/10.1109/34.608293.

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15

Mazalan, Siti Madihah, Nasrul Humaimi Mahmood, Fauzan Khairi Che Harun, Razauden Mohamed Zulkifli, and Mohd Azhar Abdul Razak. "Automated Platelet Counter Based on the Modified Hough Transform." Journal of Medical Imaging and Health Informatics 3, no. 4 (2013): 543–46. http://dx.doi.org/10.1166/jmihi.2013.1202.

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16

Zhou, Bing, and Yang He. "Fast Circle Detection Using Spatial Decomposition of Hough Transform." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 03 (2017): 1755006. http://dx.doi.org/10.1142/s0218001417550060.

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Circles are important patterns in many automatic image inspection applications. The Hough Transform (HT) is a popular method for extracting shapes from original images. It was first introduced for the recognition of straight lines, and later extended to circles. The drawbacks of standard Hough Transform (SHT) for circle detection are the large computational and storage requirements. In this paper, we propose a modified HT called Vector Quantization of Hough Transform (VQHT) to detect circles more efficiently. The basic idea is to first decompose the edge image into many subimages by using Vector Quantization (VQ) algorithm based on their natural spatial relationships. The edge points resided in each subimage are considered as one circle candidate group. Then the VQHT algorithm is applied for fast circle detection. A new paradigm to store potential curve parameters is also proposed, which can exponentially reduce the storage space for HT algorithm. Experimental results show that the proposed algorithm can quickly and accurately detect multiple circles from the noisy background.

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17

Lo, R. C., and W. H. Tsai. "Colour image detection and matching using modified generalised Hough transform." IEE Proceedings - Vision, Image, and Signal Processing 143, no. 4 (1996): 201. http://dx.doi.org/10.1049/ip-vis:19960448.

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18

Cheng, F. H., W. H. Hsu, and M. Y. Chen. "Recognition of handwritten Chinese characters by modified Hough transform techniques." IEEE Transactions on Pattern Analysis and Machine Intelligence 11, no. 4 (1989): 429–39. http://dx.doi.org/10.1109/34.19042.

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19

Ulrich, Markus, Carsten Steger, and Albert Baumgartner. "Real-time object recognition using a modified generalized Hough transform." Pattern Recognition 36, no. 11 (2003): 2557–70. http://dx.doi.org/10.1016/s0031-3203(03)00169-9.

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20

Chutatape, Opas, and Linfeng Guo. "A modified Hough transform for line detection and its performance." Pattern Recognition 32, no. 2 (1999): 181–92. http://dx.doi.org/10.1016/s0031-3203(98)00140-x.

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21

Denimal, Emmanuel, Ambroise Marin, Stéphane Guyot, Ludovic Journaux, and Paul Molin. "Automatic Biological Cell Counting Using a Modified Gradient Hough Transform." Microscopy and Microanalysis 23, no. 1 (2017): 11–21. http://dx.doi.org/10.1017/s1431927616012617.

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AbstractWe present a computational method for pseudo-circular object detection and quantitative characterization in digital images, using the gradient accumulation matrix as a basic tool. This Gradient Accumulation Transform (GAT) was first introduced in 1992 by Kierkegaard and recently used by Kaytanli & Valentine. In the present article, we modify the approach by using the phase coding studied by Cicconet, and by adding a “local contributor list” (LCL) as well as a “used contributor matrix” (UCM), which allow for accurate peak detection and exploitation. These changes help make the GAT algorithm a robust and precise method to automatically detect pseudo-circular objects in a microscopic image. We then present an application of the method to cell counting in microbiological images.

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22

Kaur, Guramarjot. "Modified Hough Transform for Road Lane Colorization to Prevent Accidents." International Journal on Recent and Innovation Trends in Computing and Communication 3, no. 1 (2015): 36–40. http://dx.doi.org/10.17762/ijritcc2321-8169.150109.

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23

Fang, Qiang. "Study of Metal Hydride Orientations by a Modified Hough Transform Algorithm." Materials Science Forum 921 (May 2018): 202–7. http://dx.doi.org/10.4028/www.scientific.net/msf.921.202.

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A modified Hough transform algorithm for the study of metal hydride orientations was developed, and optimum parameter for the transform was obtained based on numerical analysis result. By assigning an orientation to each hydride pixel, the algorithm removes the ambiguities in handling interconnected hydrides. It is expected that the algorithm will find applications in particle orientations measurement in composites and precipitation reinforced materials in general.

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24

Tian, Runlan, Guoyi Zhang, Rui Zhou, and Wei Dong. "Detection of Polyphase Codes Radar Signals in Low SNR." Mathematical Problems in Engineering 2016 (2016): 1–6. http://dx.doi.org/10.1155/2016/1382960.

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A novel effective detection method is proposed for electronic intelligence (ELINT) systems detecting polyphase codes radar signal in the low signal-to-noise ratio (SNR) scenario. The core idea of the proposed method is first to calculate the time-frequency distribution of polyphase codes radar signals via Wigner-Ville distribution (WVD); then the modified Hough transform (HT) is employed to cumulate all the energy of WVD’s ridges effectively to achieve signal detection. Compared with the generalised Wigner Hough transform (GWHT) method, the proposed method has a superior performance in low SNR and is not sensitive to the code type. Simulation results verify the validity of the proposed method.

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25

Zeng Jiankui. "Response to Comments on “Modified Hough Transform for Searching Radar Detection”." IEEE Geoscience and Remote Sensing Letters 6, no. 3 (2009): 617. http://dx.doi.org/10.1109/lgrs.2009.2019474.

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26

Habib, Ayman F., Hsiang Tseng Lin, and Michel F. Morgan. "Line-Based Modified Iterated Hough Transform for Autonomous Single-Photo Resection." Photogrammetric Engineering & Remote Sensing 69, no. 12 (2003): 1351–57. http://dx.doi.org/10.14358/pers.69.12.1351.

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27

Wang, Wantian, Yong Zhu, Ziyue Tang, et al. "Efficient Rotational Angular Velocity Estimation of Rotor Target via Modified Short-Time Fractional Fourier Transform." Remote Sensing 13, no. 10 (2021): 1970. http://dx.doi.org/10.3390/rs13101970.

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As a special micro-motion feature of rotor target, rotational angular velocity can provide a discriminant basis for target classification and recognition. In this paper, the authors focus on an efficient rotational angular velocity estimation method of the rotor target is based on the combination of the time–frequency analysis algorithm and Hough transform. In order to avoid the problems of low time–frequency resolution and cross-term interference in short-time Fourier transform and Wigner–Ville distribution algorithm, a modified short-time fractional Fourier transform (M-STFRFT) is proposed to obtain the time-FRFT domain (FRFD)-frequency spectrum with the highest time–FRFD–frequency resolution. In particular, an orthogonal matching pursuit (OMP)-based algorithm is proposed to reduce the computational complexity when estimating the matched transform order in the proposed M-STFRFT algorithm. Firstly, partial transform order candidates are selected randomly from the complete candidates. Then, a partial entropy vector corresponding to partial transform order candidates is calculated from the FRFT results and utilized to reconstruct the complete entropy vector via the OMP algorithm, and the matched transform order can be estimated by searching minimum entropy. Based on the estimated matched transform order, STFRFT is performed to obtain the time–FRFD–frequency spectrum. Moreover, Hough transform is employed to obtain the energy accumulation spectrum, and the micro-Doppler parameter of rotational angular velocity can be estimated by searching the peak value from the energy accumulation spectrum. Both simulated data and measured data collected by frequency modulated continuous wave radar validate the effectiveness of the proposed algorithm.

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28

Liu, Kun, Shu Min Fei, and Mu Lan Wang. "An Improved Randomized Hough Transform Method for the Cotton Recognition." Applied Mechanics and Materials 189 (July 2012): 383–87. http://dx.doi.org/10.4028/www.scientific.net/amm.189.383.

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The cotton recognition would become rather difficult during the application of the cotton harvesting robot (CHR) in the case where the cotton is sheltered or covered by other objects. In this paper, a novel approach of cotton detection based on the improved randomized Hough transform (IRHT) for this case is proposed. Based on the contour information from the boundary trace, the mathematic model-based IRHT is derived based on a modified circular detection technique. It yields a well agreement with the requirements of the precision and rating of CHR.

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29

Kumar, Deepak, and Dalwinder Singh. "Modified Approach of Hough Transform for Skew Detection and Correction in Documented Images." International Journal of Research in Computer Science 2, no. 3 (2012): 37–40. http://dx.doi.org/10.7815/ijorcs.23.2012.027.

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30

Chiu, Shih‐Hsuan, and Jiun‐Jian Liaw. "A proposed circle/circular arc detection method using the modified randomized hough transform." Journal of the Chinese Institute of Engineers 29, no. 3 (2006): 533–38. http://dx.doi.org/10.1080/02533839.2006.9671148.

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31

Krstinić, Damir, Ana Skelin, and Ivan Milatić. "Laser Spot Tracking Based on Modified Circular Hough Transform and Motion Pattern Analysis." Sensors 14, no. 11 (2014): 20112–33. http://dx.doi.org/10.3390/s141120112.

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32

Ploss, Peter, Stefan J. Rupitsch, and Reinhard Lerch. "Extraction of Spatial Ultrasonic Wave Packet Features by Exploiting a Modified Hough Transform." IEEE Sensors Journal 14, no. 7 (2014): 2389–95. http://dx.doi.org/10.1109/jsen.2014.2311160.

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33

Habib, Ayman F., and Rami I. Alruzouq. "Line-based modified iterated Hough transform for automatic registration of multi-source imagery." Photogrammetric Record 19, no. 105 (2004): 5–21. http://dx.doi.org/10.1111/j.0031-868x.2003.00254.x.

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34

Ünver, Halil, Yunus Kökver, Elvan Duman, and Osman Erdem. "Statistical Edge Detection and Circular Hough Transform for Optic Disk Localization." Applied Sciences 9, no. 2 (2019): 350. http://dx.doi.org/10.3390/app9020350.

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Accurate and efficient localization of the optic disk (OD) in retinal images is an essential process for the diagnosis of retinal diseases, such as diabetic retinopathy, papilledema, and glaucoma, in automatic retinal analysis systems. This paper presents an effective and robust framework for automatic detection of the OD. The framework begins with the process of elimination of the pixels below the average brightness level of the retinal images. Next, a method based on the modified robust rank order was used for edge detection. Finally, the circular Hough transform (CHT) was performed on the obtained retinal images for OD localization. Three public datasets were used to evaluate the performance of the proposed method. The optic disks were successfully located with the success rates of 100%, 96.92%, and 98.88% for the DRIVE, DIARETDB0, and DIARETDB1 datasets, respectively.

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35

Ying, Zhu, Chang Hui Li, and Wen Peng Gao. "Research on the Condom Image Detection Algorithm for Automatic Sorting." Advanced Materials Research 305 (July 2011): 315–19. http://dx.doi.org/10.4028/www.scientific.net/amr.305.315.

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To realize the automatic sorting before electrical testing of condoms, the position of condom ring needs to be discriminated with image processing method. Procedures for ellipse detection are written based on OpenCV, Gauss filter is applied to smooth the collected images, and then Canny operator is used for edge detection, combined with the modified Hough transform method to determine the ellipse center to achieve the effective detection of the condom ring.

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36

Rozhentsov, A. A., K. V. Morozov, and A. A. Baev. "Modified generalized hough transform for 3D image processing with unknown rotation and scaling parameters." Optoelectronics, Instrumentation and Data Processing 49, no. 2 (2013): 131–41. http://dx.doi.org/10.3103/s8756699013020040.

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37

Choi, Kyung-Jin, Young-Hyun Lee, Jong-Woo Moon, Chong-Kug Park, and Fumio Harashima. "Development of an Automatic Stencil Inspection System Using Modified Hough Transform and Fuzzy Logic." IEEE Transactions on Industrial Electronics 54, no. 1 (2007): 604–11. http://dx.doi.org/10.1109/tie.2006.885494.

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38

Taiwo Adeniyi, Tunde, Oladele Tinuke Omolewa, and Jide Kehinde Adeniyi. "Sclera boundary localization using circular hough transform and a modified run-data based algorithm." TELKOMNIKA (Telecommunication Computing Electronics and Control) 22, no. 3 (2024): 720. http://dx.doi.org/10.12928/telkomnika.v22i3.24588.

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39

Miroshnichenko, Sergey, Vitalii Titov, Evgenii Dremov, and Sergey Mosin. "Hough Transform Application to Digitize Rectangular Spatial Objects on Aerospace Imagery." SPIIRAS Proceedings 6, no. 61 (2018): 172–96. http://dx.doi.org/10.15622/sp.61.7.

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The paper describes the method of development for the remote sensing data processing to speed up the digitizing workflow. The method is designed to digitize rectangular objects using their approximate spatial positions and provides an automatic estimation of the orientation and aspect ratio.  The paper contains a formal statement of the problem of digitizing an object with the desired geometric shape using it’s apriori known spatial position on a source image. The method creates polygonal representations of rectangular spatial objects from one or a few reference points set by an operator. It is based on source image’s pixels clustering using spectral bands as a feature space. The following Hough transform incorporates local direction of intensity gradient to estimate object’s orientation and reduce computational complexity together with low-pass filtering within an accumulation process to improve robustness. It is shown that the developed method can be modified to digitize objects of any analytically described shape.  The method is designed to allow easy user interaction without any significant delays and to provide transparent and predictable control of an output object’s polygon size. To investigate the developed method a test dataset with more than 700 rectangular objects was used. The root-mean-square error of object’s points positioning, mean rotation error in polar coordinates and a Jaccard index were used to measure a precision of the digitized objects. The experiment results demonstrate that digitizing workflow is accelerated by 25–40% using the software implementing the developed method without a significant precision loss.

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40

Garashchenko, Aleksandr. "Methods for Auroral Oval Segmentation in Images (Part 1)." System Analysis & Mathematical Modeling 6, no. 2 (2024): 179–97. https://doi.org/10.17150/2713-1734.2024.6(2).179-197.

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The paper provides an overview of studies conducted between 2007 and 2014 on auroral oval segmentation in images. Full sky maps and ultraviolet images were used as input data. The following methods were considered: a modified version of the contour-label isolation map algorithm, the linear least squares randomized Hough transform (LLS-RHT) method, methods based on pulse-coupled neural network (PCNN), k-means histograms, adaptive minimum thresholding errors (AMET), fuzzy local information c-means (FLICM) clustering algorithm, level setting method with shape initialization and intensity adaptation.

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41

Minakov, Evgeny I., Aleksandr V. Meshkov, and Elena O. Meshkova. "Modified Hough Transform in Problem of Increasing Probability of Target Detection in Electronic Surveillance Systems." Proceedings of Universities. Electronics 24, no. 3 (2019): 291–300. http://dx.doi.org/10.24151/1561-5405-2019-24-3-291-300.

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42

Habib, Ayman, and Devin Kelley. "Automatic relative orientation of large scale imagery over urban areas using Modified Iterated Hough Transform." ISPRS Journal of Photogrammetry and Remote Sensing 56, no. 1 (2001): 29–41. http://dx.doi.org/10.1016/s0924-2716(01)00032-6.

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43

Petcher, P. A., and S. Dixon. "A modified Hough transform for removal of direct and reflected surface waves from B-scans." NDT & E International 44, no. 2 (2011): 139–44. http://dx.doi.org/10.1016/j.ndteint.2010.11.004.

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44

Rozhentsov, A. A., K. V. Morozov, and A. A. Baev. "Erratum to: “Modified generalized Hough transform for 3D image processing with unknown rotation and scaling parameters”." Optoelectronics, Instrumentation and Data Processing 49, no. 3 (2013): 320. http://dx.doi.org/10.3103/s8756699013030151.

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45

Mitra, Jubin, Abhijit Chandra, and Tanmay Halder. "Peak Trekking of Hierarchy Mountain for the Detection of Cerebral Aneurysm using Modified Hough Circle Transform." ELCVIA Electronic Letters on Computer Vision and Image Analysis 12, no. 1 (2013): 57. http://dx.doi.org/10.5565/rev/elcvia.529.

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46

Ploß, Peter, Stefan J. Rupitsch, and Reinhard Lerch. "Validation of ultrasonic beam steering accuracy for medical applications by means of a modified Hough transform." Journal of the Acoustical Society of America 134, no. 5 (2013): 4214. http://dx.doi.org/10.1121/1.4831468.

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47

Deng, Ming Hui, Qing Shuang Zeng, and Lan Ying Zhang. "An Information Fusion Algorithm Based on Dopplerlet-Hough Transformation." Advanced Materials Research 605-607 (December 2012): 2211–16. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.2211.

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In this paper, a robust image watermarking method with S-Hough transformation is proposed which is robust against geometric distortion. This watermarking is detected by a linear frequency change. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. We propose a modified Hough transformation to provide improved energy concentration of the Dopplerlet transform. The proposed scheme can resolve the time-frequency localization in a better way than the standard Dopplerlet transformation. The watermark is embedded in the 1D improved Dopplerlet transformation domains. The watermark thus generated is invisible and performs well in test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.

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48

Li, Yan, Zhi Xin Guo, and Wen Song Wei. "Path Recognition Method for Vision Navigation of Tobacco Harvester." Advanced Materials Research 605-607 (December 2012): 1502–5. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.1502.

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Tobacco harvesters are used in large-scale reclamation area. The demand for automatic navigation is urgent because of long time and intensive labor. According to the specificity of tobacco fields’ environment, the conventional path recognition method had been improved, which was taking 2G-R-B processing, threshold processing in turn and adopting dilation algorithm in image morphology instead of median blur algorithm. At last, modified Hough transform was used to extract navigation line. Processing results show that the algorithms which can be underlain in vision navigation research of tobacco machinery can meet the demand of vision navigation in tobacco fields and obtain the target navigation path rapidly and reliably.

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49

Zhang, Shou Xu, Wei Sheng Yan, Wei Chen, and Zi Li Liu. "The Visual Path Following of Autonomous Catamaran in Oil Spilling." Applied Mechanics and Materials 568-570 (June 2014): 1078–81. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.1078.

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This study aims to design a kind of autonomous oil spill collection device, more exactly, which is a collecting platform based on catamaran for the spilled oil, as catamaran has great superiorities in wave resistance and water resistance. In the whole process, visual path following is necessary, which requires quite precise local navigation; the catamaran has been controlled to run along accurately with a pre-specified path by tracking the visual landmarks on the oil fence; the algorithm for detecting the path is based on an canny operator and a modified Hough transform, which could detect the color guide line more accurate and faster.

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Zhou, Guiyuan, Jian Guo, Junyu Zhao, Qian Tang, and Zhaonan Hu. "Nanoindentation Properties of 18CrNiMo7-6 Steel after Carburizing and Quenching Determined by Continuous Stiffness Measurement Method." Metals 10, no. 1 (2020): 125. http://dx.doi.org/10.3390/met10010125.

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In this work, the nanomechanical properties involving the indentation size effect (ISE) and yield strength of a surface-modified layer of 18CrNiMo7-6 steel after case hardening were investigated via nanoindentation experiments. The experimental results showed that the hardness increased with an increase in strain rate; the contact stiffness versus indentation depth curves take the form of upper convexity due to residual compressive stress relaxation. On the basis of the Ruiz-Moreno model, a modified model considering the cutoff parameter as a function of indentation depth was proposed. This model was able to better describe the ISE of the surface-modified layer. With the Hough transform error angle of 0.1° as the critical value (h0.1° is the corresponding depth), when h > h0.1°, the yield strength calculated by the Ma model started to disperse at the depth of h0.1°. These results provide useful insight into the local mechanical properties of 18CrNiMo7-6 steel after carburizing and quenching treatment.

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