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Journal articles on the topic 'Corner points'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

Shamilov, T., and A. R. Karzhaubaeva. "EXTREMAL PROBLEM WITH CORNER POINTS." Bulletin of the Korkyt Ata Kyzylorda University 60, no. 1 (2022): 74–79. http://dx.doi.org/10.52081/bkaku.2022.v60.i1.00.

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Earlier, when considering reports on extremals with angular points, we assumed that the functions in them are continuous, and their derivatives are also continuous. But in most cases this condition is not met, and the decision is made in the form of extremals with corner points. Such reports include, for example5, a report on the reflection and refraction of extremes caused by the reflection and refraction of light. Similarly, discontinuous reports are divided into two types. In problems with a gap of the first kind, the fracture looks for extremes. In problems of the second kind, the state of

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Ahmad, Zubair, Muhammad Noman, Naveed Khan, and Saqib Murtaza. "Boundary Behavior of Conformal Maps on Domains with Corners." Babylonian Journal of Mathematics 2023 (November 19, 2023): 54–58. http://dx.doi.org/10.58496/bjm/2023/011.

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This paper investigates the behavior of conformal maps near corner points and other non-differentiable boundary points of planar domains. Conformal maps that preserve angles locally will exhibit singular behavior when approaching corners or other less smooth parts of the boundary. We classify types of isolated corner singularities and characterize the magnitude, derivatives, and integral properties of analytic functions near such points. Explicit mappings are constructed between model domains with cusps, wedges, slits, and logarithmic-type corner points. The behavior of the mapping functions i

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Gil Kang, Tok, Jae Hyon Kim, Jong Hyok Ri, and Jin Hyok Yom. "A Method to Detect Corner Points and Feature Lines Based On Edges in Images in Visual SLAM." International Journal of Advanced Networking and Applications 17, no. 01 (2025): 6761–71. https://doi.org/10.35444/ijana.2025.17107.

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Points and feature lines correctly even in different brightness and noise conditions. With the purpose of making a contribution to the improvement of the performance of ORB (Oriented FAST and Rotated BRIEF) corner detection which is widely used in SLAM system, this paper proposes a method to determine corner points and feature lines based on gradient direction changes calculated at the edge points detected in the image. First, the curve of edge points is represented by a multivalued function to be used as information about feature lines. Then, a method to detect corners on edges by examining t

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Al Nachar, Rabih, Elie Inaty, Patrick J. Bonnin, and Yasser Alayli. "A Robust Edge-Based Corner Detector (EBCD)." International Journal of Image and Graphics 14, no. 04 (2014): 1450018. http://dx.doi.org/10.1142/s0219467814500181.

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This paper presents a novel and robust edge-based corner detector (EBCD) which finds corners that are considered stable interest points in the framework of 2D object recognition especially for robot navigation. Using the EBCD, the corners are defined as intersection points of non-collinear straight image edges. The straight edge detector plus the corner detector will localize the corner positions. The detected corners have special features which are their angles and their sides length ratios. These features are invariant parameters which make the corners perfect for 2D object recognition. In a

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Nurul Ehsan Ramli, Zainor Ridzuan Yahya, and Nor Azinee Said. "Confusion Matrix as Performance Measure for Corner Detectors." Journal of Advanced Research in Applied Sciences and Engineering Technology 29, no. 1 (2022): 256–65. http://dx.doi.org/10.37934/araset.29.1.256265.

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Nowadays, corner detection algorithms have been proposed by several researchers who described them contrarily, depending on their respective viewpoints to obtain the data and information as a human eye does. Basically, no researchers have come up with a technique to compare corner detectors with another’s. Thus, this study proposed to adapt the confusion matrix technique as a performance measure for corner detectors. The judgement accuracy of every corner detector will only be pleased if the actual corner points are already known. Therefore, this study is attracted to explore the accuracy of c

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Zhou, Ran, Qing He, Jie Wu, Chao Hu, and Q. H. Meng. "Inner and Outer Eye Corners Detection for Facial Features Extraction Based on CTGF Algorithm." Applied Mechanics and Materials 58-60 (June 2011): 1966–71. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1966.

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This paper proposes a novel inner and outer eye corners detection method, which inosculates corner, regional texture and gray information, called CTGF algorithm. It utilizes corner detector to determine the candidate points of eye corners, such as Harris. Next, the region texture information is obtained through polar coordinate integral, in order to locate the exactly positions of eye corners among the candidate points. The CTGF algorithm provides a precise and reliable facial feature for many computer vision applications and the robustness and accuracy are demonstrated in experiments.

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Sanders, D. A., G. Lambert, and L. Pevy. "Pre-locating corners in images in order to improve the extraction of Fourier descriptors and subsequent recognition of shipbuilding parts." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 223, no. 9 (2009): 1217–23. http://dx.doi.org/10.1243/09544054jem1553sc.

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Improvements are described for a pattern recognition system for recognizing shipbuilding parts. This is achieved by using a new simple and accurate corner finder. The new system initially finds corners in an edge detected image of a ship's part and uses that new information to extract Fourier descriptors to feed into a neural network to make decisions about shapes. Results show that the new corner finder was better at distinguishing between various ships' parts than other corner finders and proved to be a valid approach. The new corner finding technique uses a bottom-up approach to find corner

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Xu, Yanlei, Run He, Zongmei Gao, Chenxiao Li, Yuting Zhai, and Yubin Jiao. "Weed Density Detection Method Based on Absolute Feature Corner Points in Field." Agronomy 10, no. 1 (2020): 113. http://dx.doi.org/10.3390/agronomy10010113.

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Field weeds identification is challenging for precision spraying, i.e., the automation identification of the weeds from the crops. For rapidly obtaining weed distribution in field, this study developed a weed density detection method based on absolute feature corner point (AFCP) algorithm for the first time. For optimizing the AFCP algorithm, image preprocessing was firstly performed through a sub-module processing capable of segmenting and optimizing the field images. The AFCP algorithm improved Harris corner to extract corners of single crop and weed and then sub-absolute corner classifier a

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9

Anandhalli, Mallikarjun, and Vishwanath P. Baligar. "An Approach to Detect Vehicles in Multiple Climatic Conditions Using the Corner Point Approach." Journal of Intelligent Systems 27, no. 3 (2018): 363–76. http://dx.doi.org/10.1515/jisys-2016-0073.

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Abstract This paper presents a new method of detecting vehicles by using a simple and effective algorithm. The features of a vehicle are the most important aspects in detection of vehicles. The corner points are considered for the proposed algorithm. A large number of points are densely packed within the area of a vehicle, and the points are calculated by using the Harris corner detector. Making use of the fact that they are densely packed, grouping of these points is carried out. This grouping indicates that the group of corners belongs to each vehicle, and such groupings play a vital role in

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10

Irshad, Misbah, Irfa Elahi, and Malik Zawwar Hussain. "Detecting Corners for 3D Objects." International Journal of Computer Vision and Image Processing 1, no. 4 (2011): 59–68. http://dx.doi.org/10.4018/ijcvip.2011100105.

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In this paper, a corner detection algorithm for 3D objects is presented. This algorithm is an extension of corner detection scheme for planar objects (Chetrikov &amp; Zsabo, 1999). This algorithm finds corners and other high curvature points for 3D objects.

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11

Guo, Yong Fang, Ming Yu, and Yi Cai Sun. "Study on a Real-Time Corner Detection Algorithm." Advanced Materials Research 159 (December 2010): 192–97. http://dx.doi.org/10.4028/www.scientific.net/amr.159.192.

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Conventional Harris corner detector is a desirable detector but it requires significantly more computation time. For MIC detector proposed by Trajkovic, the minimal computational demands of its operator make it well-suited for real-time applications, however the Trajkovic’s operator responses too readily to certain diagonal edges. For this reason, the paper proposed a new corner detection algorithm. The new corner detection algorithm adopted multigrid algorithm and preprocessed the lower resolution revision of the original image to obtain the potential corners, subsequently used autocorrelatio

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12

Zhang, Xin, and Xiu Hua Ji. "An Improved Harris Corner Detection Algorithm for Noised Images." Advanced Materials Research 433-440 (January 2012): 6151–56. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.6151.

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The Harris corner detection algorithm is widely applied in image mosaic, which is simple and stable. However, the algorithm has a disadvantage that it obtains a lot of false corners when there exist some noise in an image. An improved Harris corner detection algorithm is proposed in this paper. The new algorithm reduces the noise impact greatly. The experimental results show that the improved algorithm not only reduces false corner points greatly, but also retain the majority of true corners. As a result, it improves the detection accuracy and reduces the chance of error matching in image regi

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Sun, Liang, Jian Chun Xing, Shuang Qing Wang, and Shi Qiang Wang. "A Self-Adaptive Corner Detection Algorithm for Low-Contrast Images." Applied Mechanics and Materials 615 (August 2014): 158–64. http://dx.doi.org/10.4028/www.scientific.net/amm.615.158.

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In order to effectively inhibit the image dithering caused by wind-induced vibration in the security monitoring system, it calls for the extraction and match of the feature points of the sequential frames. Harris corner detection algorithm is a widely-employed characteristics extraction algorithm in the image processing. In the security monitoring field, images and videos photographed are characterized by large scale, high pixel and low contrast degree. The classical algorithm often fails to effectively obtain the feature points while handling the images and videos of the kind. Concerning the

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Tahir, Mehwish, Nadia Kanwal, and Fatima Anjum. "FAB: Fast Angular Binary Descriptor for Matching Corner Points in Video Imagery." Journal of Robotics 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/3458207.

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Image matching is a fundamental step in several computer vision applications where the requirement is fast, accurate, and robust matching of images in the presence of different transformations. Detection and more importantly description of low-level image features proved to be a more appropriate choice for this purpose, such as edges, corners, or blobs. Modern descriptors use binary values to store neighbourhood information of feature points for matching because binary descriptors are fast to compute and match. This paper proposes a descriptor called Fast Angular Binary (FAB) descriptor that i

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15

Song, Weigang, Baojiang Zhong, and Xun Sun. "Building Corner Detection in Aerial Images with Fully Convolutional Networks." Sensors 19, no. 8 (2019): 1915. http://dx.doi.org/10.3390/s19081915.

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In aerial images, corner points can be detected to describe the structural information of buildings for city modeling, geo-localization, and so on. For this specific vision task, the existing generic corner detectors perform poorly, as they are incapable of distinguishing corner points on buildings from those on other objects such as trees and shadows. Recently, fully convolutional networks (FCNs) have been developed for semantic image segmentation that are able to recognize a designated kind of object through a training process with a manually labeled dataset. Motivated by this achievement, a

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Dantas, Marrone Silvério Melo, Daniel Bezerra, Assis T. de Oliveira Filho, et al. "Automatic Template Detection for Camera Calibration." Research, Society and Development 11, no. 14 (2022): e173111436168. http://dx.doi.org/10.33448/rsd-v11i14.36168.

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Camera calibration is the process of extract the intrinsic and extrinsic parameters of a camera. Those parameters guide the 3-dimensional localization into relation to the 2-dimensional space from the images acquired by the camera. The 3-dimensional correlation can be generated with an object with known measures, being the most common checkerboard for this purpose. From these checker- boards, the usual approach extracts the position of the inner points, equivalent to the corners of the squares, to generate this correlation. A broad range of algorithms tries to ﬁnd those points on the image. St

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Wang, Wei, Yi Zhang, Gengyu Ge, Huan Yang, and Yue Wang. "A New Approach toward Corner Detection for Use in Point Cloud Registration." Remote Sensing 15, no. 13 (2023): 3375. http://dx.doi.org/10.3390/rs15133375.

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For this study, a new point cloud alignment method is proposed for extracting corner points and aligning them at the geometric level. It can align point clouds that have low overlap and is more robust to outliers and noise. First, planes are extracted from the raw point cloud, and the corner points are defined as the intersection of three planes. Next, graphs are constructed for subsequent point cloud registration by treating corners as vertices and sharing planes as edges. The graph-matching algorithm is then applied to determine correspondence. Finally, point clouds are registered by alignin

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18

Wei, Yang, Yang Xu, Gaofei Wang, Xunyu Cheng, and Guofen Li. "Influence of the Cross-Sectional Shape and Corner Radius on the Compressive Behaviour of Concrete Columns Confined by FRP and Stirrups." Polymers 14, no. 2 (2022): 341. http://dx.doi.org/10.3390/polym14020341.

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Axial compression tests were carried out on 72 FRP (fiber reinforced polymer)–stirrup composite-confined concrete columns. Stirrups ensure the residual bearing capacity and ductility after the FRP fractures. To reduce the effect of stress concentration at the corners of the confined square-section concrete columns and improve the restraint effect, an FRP–stirrup composite-confined concrete structure with rounded corners is proposed. Different corner radii of the stirrup and outer FRP were designed, and the corner radius of the stirrup was adjusted accurately to meet the designed corner radius

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19

Al-Azzawy, Dhyaa. "Points Descriptor in Pattern Recognition: A New Approach." Iraqi Journal for Computers and Informatics 43, no. 2 (2017): 23–29. http://dx.doi.org/10.25195/ijci.v43i2.60.

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We presented in the paper a new tactic, the first thing we have done is extracting the points of descriptor,which it is used in pattern recognition, especially in detection of corner algorithm. Scales of samples (images),each image is tuned by a factor (scale), collect the corners, and collect the points of descriptor key in thesecollected corners, in other words; Hough Transform uses the collected descriptors for classification process, andclassify each points of image to its equivalence class. Experimentally, by using MATLAB, we are shown highaccuracy of recognition result on the selected sa

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20

Chen, Ming Ming, Zhi Yong Lei, and Ming Lei. "Study on Image Corner Extraction Based on the Improved Canny Edge Detector." Applied Mechanics and Materials 433-435 (October 2013): 273–76. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.273.

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In computer vision system, the corners position need to be extracted from plane plate image. This paper presented a novel algorithm that improved the accuracy of corner detection from pixel to sub-pixel. The Canny operator was used to detect the corner edge pixels, and Gaussian filter was substituted by the bilateral filtering. It can remove noise and retain more slight edge information. Then, the corner edge pixels were transformed by Zernike moment and the sub-pixel edges of the corner were getted. Finally these sub-pixel edge points were linearly fitted and it was resulted in the corner coo

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21

Jiao, N., W. Kang, Y. Xiang, and H. You. "A NOVEL AND FAST CORNER DETECTION METHOD FOR SAR IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 13, 2017): 605–8. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-605-2017.

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Corners play an important role on image processing, while it is difficult to detect reliable and repeatable corners in SAR images due to the complex property of SAR sensors. In this paper, we propose a fast and novel corner detection method for SAR imagery. First, a local processing window is constructed for each point. We use the local mean of a 3 x 3 mask to represent a single point, which is weighted by a Gaussian template. Then the candidate point is compared with 16 surrounding points in the processing window. Considering the multiplicative property of speckle noise, the similarity measur

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Raseli, Siti Sarah, Afina Amirhussain, and Norpah Mahat. "Corner Point Detection for The Map of Kariah Kg. Bukit Kapar." Mathematical Sciences and Informatics Journal 1, no. 2 (2020): 51–58. http://dx.doi.org/10.24191/mij.v1i2.14186.

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Corner point detection are the important technique for many image processing applications including image enhancement, object detection and pattern recognition. The purpose of this study is to detect the corner points of a map of Kariah Kampung Bukit Kapar image by using Harris Corner Detector. Corner points in an image represents a lot of important information of the image. Detection of corner points accurately is significant to image processing, which can reduce much of the calculations. In this study, the initial technique is smoothing the image and extract the boundary of the image. Then,

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Chen, Chen, Liandong Yu, Huakun Jia, et al. "Research on Path Smoothing Method for Robot Scanning Measurement Based on Multiple Curves." Actuators 14, no. 3 (2025): 135. https://doi.org/10.3390/act14030135.

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As the field of robotics advances swiftly, industrial automation has become prevalent in the realms of manufacturing and precision measurement. In robot measurement applications, the original path often originates from the discrete output of CAD models or point cloud data of vision systems, and its measurement path is a linear path composed of discrete feature points. Vibrations are generated by robots when passing through corners between adjacent linear segments. In order to reduce vibration, an algorithm for smoothing the robot’s measurement path based on multiple curves is proposed. Based o

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Zhang, Guang Bin, Hong Chun Shu, and Ji Lai Yu. "An Approach of Wavefront Identification for Traveling Wave Fault Location Based on Harris Corner Detector." Advanced Materials Research 960-961 (June 2014): 1100–1103. http://dx.doi.org/10.4028/www.scientific.net/amr.960-961.1100.

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Wavefront identification is important for traveling based fault location. In order to improve its reliability, a novel wavefront identification method based on Harris corner detector has been proposed in this paper. The principle of single-ended traveling wave fault location was briefly introduced at first, and the features of wavefronts generated by faults on transmission lines were analyzed. The arrival of traveling waves' wavefronts is considered as corner points in digital image of waveshape. The corner points can be extracted precisely by Harris corner detector, and both false corner poin

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Liu, Yiting, Lianjie Sui, Peijuan Li, et al. "A Radar Linear Feature Fitting Algorithm Combining Adaptive Clustering and Corner Detection Operator." Journal of Sensors 2023 (February 24, 2023): 1–17. http://dx.doi.org/10.1155/2023/6991467.

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The precise environmental parameters derived from laser radar scan data can significantly accelerate the process of real-time localization and map-matching technique. One of the research directions is autonomous navigation algorithm based on LiDAR slam. LiDAR has the advantage of having a wide range of accuracy and distance. However, due to the limited amount of LiDAR data available and the influence of sensor noise, it is easy to run into issues such as low accuracy of robot map construction or large positioning errors. At the moment, most of feature extraction algorithms employ an iterative

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Koretz, Ronald L. "The Reading Corner. V. End Points." Nutrition in Clinical Practice 13, no. 6 (1998): 291–94. http://dx.doi.org/10.1177/088453369801300605.

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Li, Xuyang, Xuemei Xie, Mingxuan Yu, Jiakai Luo, Chengwei Rao, and Guangming Shi. "Gradient Corner Pooling for Keypoint-Based Object Detection." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 2 (2023): 1460–67. http://dx.doi.org/10.1609/aaai.v37i2.25231.

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Detecting objects as multiple keypoints is an important approach in the anchor-free object detection methods while corner pooling is an effective feature encoding method for corner positioning. The corners of the bounding box are located by summing the feature maps which are max-pooled in the x and y directions respectively by corner pooling. In the unidirectional max pooling operation, the features of the densely arranged objects of the same class are prone to occlusion. To this end, we propose a method named Gradient Corner Pooling. The spatial distance information of objects on the feature

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Yang, Xuefeng, and Youpeng You. "Linear Tool Path-Smoothing Method in High-Speed Machining Based on Error Feasible Area and Curvature Optimization." Applied Sciences 12, no. 19 (2022): 9443. http://dx.doi.org/10.3390/app12199443.

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Linear tool path is widely used in high-speed NC machining. However, the geometrical discontinuity of the corner between the linear tool paths will lead to fluctuations in speed, acceleration and jerk, which can excite machinery vibration and reduce the machining efficiency and surface quality. To solve these problems, a novel corner smoothing method based on error feasible area and curvature optimization is proposed in this paper. Compared with most traditional corner smoothing methods using higher-order curves with all control points lying in the straight segment and inside of the tool path,

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Jung, J., K. Bang, G. Sohn, and C. Armenakis. "MATCHING AERIAL IMAGES TO 3D BUILDING MODELS BASED ON CONTEXT-BASED GEOMETRIC HASHING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 1, 2016): 17–23. http://dx.doi.org/10.5194/isprsannals-iii-1-17-2016.

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In this paper, a new model-to-image framework to automatically align a single airborne image with existing 3D building models using geometric hashing is proposed. As a prerequisite process for various applications such as data fusion, object tracking, change detection and texture mapping, the proposed registration method is used for determining accurate exterior orientation parameters (EOPs) of a single image. This model-to-image matching process consists of three steps: 1) feature extraction, 2) similarity measure and matching, and 3) adjustment of EOPs of a single image. For feature extracti

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Jung, J., K. Bang, G. Sohn, and C. Armenakis. "MATCHING AERIAL IMAGES TO 3D BUILDING MODELS BASED ON CONTEXT-BASED GEOMETRIC HASHING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 1, 2016): 17–23. http://dx.doi.org/10.5194/isprs-annals-iii-1-17-2016.

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In this paper, a new model-to-image framework to automatically align a single airborne image with existing 3D building models using geometric hashing is proposed. As a prerequisite process for various applications such as data fusion, object tracking, change detection and texture mapping, the proposed registration method is used for determining accurate exterior orientation parameters (EOPs) of a single image. This model-to-image matching process consists of three steps: 1) feature extraction, 2) similarity measure and matching, and 3) adjustment of EOPs of a single image. For feature extracti

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Dan, Xizuo, Qicheng Gong, Mei Zhang, Tao Li, Guihua Li, and Yonghong Wang. "Chessboard Corner Detection Based on EDLines Algorithm." Sensors 22, no. 9 (2022): 3398. http://dx.doi.org/10.3390/s22093398.

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To improve the robustness and accuracy of the corner-detection algorithm, this paper proposes a camera-calibration method based on the EDLines algorithm for the automatic detection of chessboard corners. The EDLines algorithm is initially used to perform straight-line detection on the calibration image. The features of the broken straight lines at the corners are then used to filter the straight lines and remove the background straight lines outside the chessboard. The pixels in the rectangular area around the filtered straight line are sorted by the gray gradient. After using the sorted resul

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Naurin, Afrin, and Lai Wei. "Effective Interest Region Estimation Model to Represent Corners for Image." Signal & Image Processing: An International Journal (SIPIJ) 9, no. 6 (2019): 29–38. https://doi.org/10.5281/zenodo.2564897.

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One of the most important steps to describe local features is to estimate the interest region around the feature location to achieve the invariance against different image transformation. The pixels inside the interest region are used to build the descriptor, to represent a feature. Estimating the interest region around a corner location is a fundamental step to describe the corner feature. But the process is challenging under different image conditions. Most of the corner detectors derive appropriate scales to estimate the region to build descriptors. In our approach, we have proposed a new l

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Naurin, Afrin, and Lai Wei. "Effective Interest Region Estimation Model to Represent Corners for Image." Signal & Image Processing: An International Journal (SIPIJ) 9, no. 6 (2019): 29–38. https://doi.org/10.5281/zenodo.3445795.

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One of the most important steps to describe local features is to estimate the interest region around the feature location to achieve the invariance against different image transformation. The pixels inside the interest region are used to build the descriptor, to represent a feature. Estimating the interest region around a corner location is a fundamental step to describe the corner feature. But the process is challenging under different image conditions. Most of the corner detectors derive appropriate scales to estimate the region to build descriptors. In our approach, we have proposed a new l

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Hou, Jue, Bugao Xu, Hanchao Gao, and RongWu Wang. "Measuring fiber orientations in nonwoven web images using corner detection by Bézier fitting curves." Textile Research Journal 88, no. 18 (2017): 2120–31. http://dx.doi.org/10.1177/0040517517716904.

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This paper describes a novel method for measuring fiber orientations in nonwoven web images by using Bézier fitting curves to detect corners of fiber edges and to separate crossing fiber edges. First, the Canny detector was adopted to extract fiber edges. Second, Bézier curve fitting was used to fit each fiber edge for calculating the curvature of every point on the edge. Third, corner points were detected by locating points where the curvatures were minimal on various edges and below the threshold to divide edges into segments for orientation calculations. Last, a formula calculating the fibe

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Sarfraz, M., and Z. N. K. Swati. "Mining Corner Points on the Generic Shapes." Open Journal of Applied Sciences 03, no. 01 (2013): 10–15. http://dx.doi.org/10.4236/ojapps.2013.31b003.

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Ghosh, Mridul, and Debotosh Bhattacharjee. "Human Identification by Gait Using Corner Points." International Journal of Image, Graphics and Signal Processing 4, no. 2 (2012): 30–36. http://dx.doi.org/10.5815/ijigsp.2012.02.05.

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Zhang, Changlong, Miaomiao Wang, Yong Li, and Xuesong Yang. "Nearest Neighbour Corner Points Matching Detection Algorithm." MATEC Web of Conferences 22 (2015): 01035. http://dx.doi.org/10.1051/matecconf/20152201035.

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ZHENG, ZHIGANG, ZHENGJUN ZHA, LONG HAN, and ZENGFU WANG. "FEATURE DETECTION AND CORRESPONDENCE FOR CAMERA CALIBRATION." International Journal of Information Acquisition 05, no. 01 (2008): 41–50. http://dx.doi.org/10.1142/s021987890800148x.

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This paper addresses the problem of highly accurate, highly speedy, more reliable and fully automatic camera calibration. Our objective is to construct a reliable and fully automatic system to supply a more robust and highly accurate calibration scheme. A checkerboard pattern is used as calibration pattern. After the corner points on image are detected, an improved Delaunay triangulation based algorithm is used to make correspondences between corner points on image and corner points on checkerboard in 3D space. In order to determine precise position of the actual corner points, a geometrical c

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Ying, Jie, Yan Bin Song, and Lin Li Lu. "Research on Panorama Generation Based on Homography Estimation." Applied Mechanics and Materials 423-426 (September 2013): 2518–21. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.2518.

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An improved panorama generation method based on homography estimation was proposed. Corners detection were realized using FAST algorithm. After corner detection, the related corners were matched and homography estimation was established. Using random sample consensus related estimation, we got accurate interior points to estimate parameters. Image fusion was realized using hybrid filter operator. Experimental results showed that the panorama generation method based on homography estimation is effective and robust.

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Ahmad, Daud, Kiran Naz, Mariyam Ehsan Buttar, Pompei C. Darab, and Mohammed Sallah. "Extremal Solutions for Surface Energy Minimization: Bicubically Blended Coons Patches." Symmetry 15, no. 6 (2023): 1237. http://dx.doi.org/10.3390/sym15061237.

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A Coons patch is characterized by a finite set of boundary curves, which are dependent on the choice of blending functions. For a bicubically blended Coons patch (BBCP), the Hermite cubic polynomials (interpolants) are used as blending functions. A BBCP comprises information about its four corner points, including the curvature represented by eight tangent vectors, as well as the twisting behavior determined by the four twist vectors at these corner points. The interior shape of the BBCP depends not only on the tangent vectors at the corner points but on the twist vectors as well. The alterati

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Wanchun, Sun, and Zhang Jianxun. "An improved corner detection algorithm used in video statistics." Journal of Algorithms & Computational Technology 13 (November 19, 2018): 174830181881348. http://dx.doi.org/10.1177/1748301818813485.

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In order to address the difficult problem to determine the number of populations, this paper improves the algorithm based on the Harris point detection algorithm, and the number of people is returned through the first-order linear regression model. First of all, according to the shortcomings of Harris corner algorithm in population statistics, an adaptive gray difference idea is proposed, and the concept of integral image is introduced to overcome its defects in noise immunity and real-time operation. Secondly, in view of the large error generated in the process of population statistics in the

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Arslan, Abdullah N. "Identifying All Matches of a Rigid Object in an Input Image Using Visible Triangles." Mathematics 13, no. 6 (2025): 925. https://doi.org/10.3390/math13060925.

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It has been suggested that for objects identifiable by their corners, every triangle formed by these corner points can serve as a reference for detecting other corner points. This approach enables effective rigid object detection, including partial matches. However, when there are many corner points, the implementation becomes impractical due to excessive memory requirements. To overcome this, we propose a new algorithm that leverages Delaunay triangulation, considering only the triangles generated by the Delaunay triangulation to reduce the complexity of the original approach. Our algorithm i

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Wang, Yifan, Yang Li, Jiaqi Wang, Haofeng Lv, and Zeli Yang. "A Target Corner Detection Algorithm Based on the Fusion of FAST and Harris." Mathematical Problems in Engineering 2022 (April 2, 2022): 1–16. http://dx.doi.org/10.1155/2022/4611508.

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Corner detection is a common method to obtain image features, and the detection effect influences the performance of matching and tracking directly. A FAST-Harris fusion corner detection algorithm is proposed to improve the shortcomings of the Harris algorithm, such as the low detection accuracy and low positioning accuracy, and a corner detection fusion model is established. First, the detected target image is padded, and then the FAST algorithm is used with a 25% reduced contrast points to achieve fast capture roughly; in this way, a candidate corner set is obtained. Then, screening the cand

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Krzyżek, Robert. "Evaluating the Accuracy of Determining Coordinates of a Corner of a Building Measured in the RTN GNSS Mode, Having Applied the Innovative Algorithm of Vector Translation." Reports on Geodesy and Geoinformatics 103, no. 1 (2017): 10–21. http://dx.doi.org/10.1515/rgg-2017-0002.

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Abstract The study evaluates the accuracy of determining coordinates of a corner of a building measured in the RTN GNSS mode (Real Time Network Global Navigation Satellite System) using the method of line-line intersection and having applied the algorithm of vector translation, developed by the author. The performed analysis of accuracy proved a high precision in determining the points subjected to studies. An important factor in the formation of a mean error regarding the position of the corner of a building, having used the algorithm of vector translation, is the assumption of correctness of

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Ercan, M. Fikret, and Ricky Ben Wang. "Computer Vision-Based Inspection System for Worker Training in Build and Construction Industry." Computers 11, no. 6 (2022): 100. http://dx.doi.org/10.3390/computers11060100.

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Recently computer vision has been applied in various fields of engineering successfully ranging from manufacturing to autonomous cars. A key player in this development is the achievements of the latest object detection and classification architectures. In this study, we utilized computer vision and the latest object detection techniques for an automated assessment system. It is developed to reduce the person-hours involved in worker training assessment. In our local building and construction industry, workers are required to be certificated for their technical skills in order to qualify workin

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Jiang, Zetao, Xing Yu, and Le Zhou. "A Method of Enhanced Corner Points Extraction Based on Circular Neighborhood." International Journal of Computer and Electrical Engineering 6, no. 4 (2014): 299–302. http://dx.doi.org/10.7763/ijcee.2014.v6.842.

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Ma, Haoran, Bei Peng, Guochuan Zhao, Shuang Wang, Yun Rong, and Yibo Li. "Grain Truck Compartment Localization Method based on Point Cloud Projection." Measurement Science Review 25, no. 2 (2025): 64–71. https://doi.org/10.2478/msr-2025-0009.

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Abstract Quality control is an essential step before grain storage. It requires the localization of grain truck compartments and guiding robotic arms to automatically sample grains. However, the diverse types of grain trucks and the variability in parking lead to difficulties in compartment localization and inaccurate measurements. To solve this problem, a rotating 3D laser scanner is proposed to scan grain trucks. After ground calibration, the XOY plane of the rotating scanned point cloud is aligned parallel to the ground. To avoid complex point cloud segmentation, grain truck point clouds ar

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Veremeychyk, O. M. "THE ASSEMBLAGES OF THE ROMNY CULTURE ON THE SETTLEMENT ZAMKOVA HORA." Archaeology and Early History of Ukraine 44, no. 3 (2022): 292–303. http://dx.doi.org/10.37445/adiu.2022.03.18.

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This paper is devoted to the assemblages of the Romny culture discovered in the settlement Zamkova Hora in Lubech. Three residential buildings in total were excavated. One of them was discovered by the expedition of Academician Boris Rybakov, the other two buildings were excavated by the expedition headed by the author. They were located in one row, along the long axis of the settlement at a distance of about 10—12 m from its south-eastern edge. The most northern building was excavated in 2011. Its 4 Ч 4 subsquare pit is oriented by corners on the cardinal points and deepened into the vi

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Lailiyatul, Amanda, Agus Qowiyuddin, and Khoirul Huda. "Analysis Analysis of the ability to understand junior high school mathematics concepts in the material of quadrilaterals." Jurnal Riset Pendidikan Matematika Jakarta 6, no. 1 (2024): 1–8. http://dx.doi.org/10.21009/jrpmj.v6i1.29021.

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Build a flat quadrangle It is a certain line segment which is joined by four points where the points are not in a line, which in pairs meet at the ends and each line segment must meet with two corners which are formed called the corners in a quadrilateral with the corner points being the four points the. Quadrilateral shapes include squares, rectangles, parallelograms, rhombuses, kites and trapezoids. (Nadjib, 2014) The aim of this research is to determine and describe the ability to understand mathematical concepts of rectangular flat shapes at Al-Hidayah Sukorejo Middle School Class VII. The

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Oláh, Roland, Péter Hajós, Zsuzsanna Soós, and Gábor Winkler. "De Quervain thyroiditis. Corner points of the diagnosis." Orvosi Hetilap 155, no. 17 (2014): 676–80. http://dx.doi.org/10.1556/oh.2014.29865.

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Inflammatory disorders of the thyroid gland are divided into three groups according to their duration (acute, subacute and chronic). De Quervain’s thyroiditis (also termed giant cell or granulomatous thyroiditis) is a subacute inflammation of the thyroid, which accounts for 5% of thyroid disorders. The etiology is unknown, it usually appears two weeks after an upper viral respiratory infection. The clinical feature includes neck pain, which is aggraviated during swallowing, and radiates to the ear. On palpation, the thyroid is exquisitely tender. The erythrocyte sedimentation rate is markedly

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