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Journal articles on the topic 'Binocular vision. Image processing Image analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

Cheng, Ruoshi, Caixia Zhang, Qingyang Xu, et al. "Underwater Fish Body Length Estimation Based on Binocular Image Processing." Information 11, no. 10 (2020): 476. http://dx.doi.org/10.3390/info11100476.

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Recently, the information analysis technology of underwater has developed rapidly, which is beneficial to underwater resource exploration, underwater aquaculture, etc. Dangerous and laborious manual work is replaced by deep learning-based computer vision technology, which has gradually become the mainstream. The binocular cameras based visual analysis method can not only collect seabed images but also construct the 3D scene information. The parallax of the binocular image was used to calculate the depth information of the underwater object. A binocular camera based refined analysis method for underwater creature body length estimation was constructed. A fully convolutional network (FCN) was used to segment the corresponding underwater object in the image to obtain the object position. A fish’s body direction estimation algorithm is proposed according to the segmentation image. The semi-global block matching (SGBM) algorithm was used to calculate the depth of the object region and estimate the object body length according to the left and right views of the object. The algorithm has certain advantages in time and accuracy for interest object analysis by the combination of FCN and SGBM. Experiment results show that this method effectively reduces unnecessary information, improves efficiency and accuracy compared to the original SGBM algorithm.

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Zhang, Jing, Ru Gao, Chun Yan Liu, and Ya Wei Zhao. "Research on 3D Modeling System Based on Binocular Vision Image Acquisition." Applied Mechanics and Materials 385-386 (August 2013): 640–43. http://dx.doi.org/10.4028/www.scientific.net/amm.385-386.640.

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Three-dimensional modeling of the image acquisition system based on binocular computer vision scanning system scene with MCU processing the two-dimensional image data collected by the CCD sensor, and complete the image binarization processing using hardware, to improve the efficiency of the image processing; using timing delay analysis circuit the edge of the identification image characteristics, the data amount of the compression of the image processing; will be collected by the CCD sensor the two-dimensional image data transmission to a computer, thereby effectively shortening the transmission time of the data.

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Lv, Xue Zhi, Mei Ting Wang, Yong Feng Qi, Xue Mei Zhao, and Hao Dong. "Research on Ranging Method Based on Binocular Stereo Vision." Advanced Materials Research 945-949 (June 2014): 2075–81. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.2075.

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Binocular stereo vision ranging method taking contour boundary center of measurement object as matching features was investigated. And experimental platform for binocular stereo vision ranging system was built up. The stereo vision ranging system comprised four modules: camera calibration, stereo calibration, stereo rectification and features extraction. Firstly, the intrinsic parameters of single camera were obtained by camera calibration and relative pose of two cameras was obtained by stereo calibration. Then the left and right images were rectified into a frontal parallel arrangement by Bouguet’s method. The edge pixels of contours were detected by image processing. Then the disparity and the distance was calculated taking contour center as matching features. Finally, measurement error analysis was performed to verify the proposed method with good practicability.

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Makarenko, A. A., and L. A. Vinokurov. "Application of digital image processing for autofocusing system construction." Radio industry (Russia) 30, no. 2 (2020): 69–79. http://dx.doi.org/10.21778/2413-9599-2020-30-2-69-79.

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The article states the method of autofocusing of the optoelectronic image, based on digital image processing. Some systems of autofocusing which can be used in optoelectronic equipment of unmanned aerial vehicles are considered. The method developed by authors and the program algorithm implementing it are similar to the rules of functioning of an element of the human visual system which executes an estimation of a spectrum of spatial frequencies for the realization of focusing of the image of objects which are of interest or danger and are on different distance from the observer. The best focusing is defined on the greatest width of a spectrum of spatial frequencies of the object. Such estimation allows focusing the necessary object on the observable image even in the absence of binocular vision. The method is based on the numerical analysis of a two-dimensional amplitude spectrum of the image. Results of operation of the stated method which confirm its efficiency are presented.

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Liu, Shuang, Xiang Jie Kong, and Ming Cai Shan. "Vehicle Security Distance Control Based on Binocular Parallax Vision." Applied Mechanics and Materials 644-650 (September 2014): 207–10. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.207.

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Binocular parallax vision system is a kind of computer vision technology. Two cameras on different locations can get two different pictures of same object. The space position of the object can be calculated by the parallax information of two different pictures. The binocular parallax vision technology includes cameras calibration, image processing, and stereo matching analysis. The paper will introduce the inside and outside parameters calibration methods, and combing the traffic applications, designed the calibrating scheme. The parameters that obtained according to the scheme can meet the demands of measuring the vehicle distance. The high precision can meet the needs of intelligent transportation vehicles in a security vehicles spacing survey, which is an effective way for measuring the front car distance.

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Lin, Yu-Hsien, Shao-Yu Chen, and Chia-Hung Tsou. "Development of an Image Processing Module for Autonomous Underwater Vehicles through Integration of Visual Recognition with Stereoscopic Image Reconstruction." Journal of Marine Science and Engineering 7, no. 4 (2019): 107. http://dx.doi.org/10.3390/jmse7040107.

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This study investigated the development of visual recognition and stereoscopic imaging technology, applying them to the construction of an image processing system for autonomous underwater vehicles (AUVs). For the proposed visual recognition technology, a Hough transform was combined with an optical flow algorithm to detect the linear features and movement speeds of dynamic images; the proposed stereoscopic imaging technique employed a Harris corner detector to estimate the distance of the target. A physical AUV was constructed with a wide-angle lens camera and a binocular vision device mounted on the bow to provide image input. Subsequently, a simulation environment was established in Simscape Multibody and used to control the post-driver system of the stern, which contained horizontal and vertical rudder planes as well as the propeller. In static testing at National Cheng Kung University, physical targets were placed in a stability water tank; the study compared the analysis results obtained from various brightness and turbidity conditions in out-of-water and underwater environments. Finally, the dynamic testing results were combined with a fuzzy controller to output the real-time responses of the vehicle regarding the angles, rates of the rudder planes, and the propeller revolution speeds at various distances.

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7

Shi, Wenxiong, Qi Zhang, Huimin Xie, and Wei He. "A Binocular Vision-Based 3D Sampling Moiré Method for Complex Shape Measurement." Applied Sciences 11, no. 11 (2021): 5175. http://dx.doi.org/10.3390/app11115175.

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As a promising method for moiré processing, sampling moiré has attracted significant interest for binocular vision-based 3D measurement, which is widely used in many fields of science and engineering. However, one key problem of its 3D shape measurement is that the visual angle difference between the left and right cameras causes inconsistency of the fringe image carrier fields, resulting in the phase mismatch of sampling moiré. In this paper, we developed a phase correction method to solve this problem. After epipolar rectification and carrier phase introduction and correction, the absolute phase of the fringe images was obtained. A more universal 3D sampling moiré measurement can be achieved based on the phase match and binocular vision model. Our numerical simulation and experiment showed the high robustness and anti-noise ability of this new 3D sampling moiré method for high-precision 3D shape measurement. As an application, cantilever beams are fabricated by directed energy deposition (DED) using different process parameters, and their 3D deformation caused by residual stresses is measured, showing great potential for residual stress analyses during additive manufacturing.

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Frolov, M. M., and M. I. Truphanov. "OPTICAL-ELECTRONIC DEVICE OF CALCULATION OF PARAMETERS OF VOLUME OBJECTS OF WORKING SCENE AT MULTIPLE SOURCES OF VIDEO DATA." Proceedings of the Southwest State University 22, no. 6 (2019): 198–205. http://dx.doi.org/10.21869/2223-1560-2018-22-6-198-205.

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The paper considers approaches to the construction of a geographically distributed optical-electronic device, providing an analysis of significant and long working scenes in the interests of automating the processes of control and management of robotic tools in industrial assembly shops and warehouses. The principal difference of the proposed solution is the possibility of obtaining images of the analyzed objects using optical-electronic sensors located in different parts of the workspace to realize the function of binocular vision on a much larger area of the working scene compared to analogues. A distinctive novelty of the developed theoretical approach is the approach to binocular technical vision, which consists in iteratively performing calibration procedures for selected pairs of opticalelectronic sensors and the subsequent calculation of the spatial coordinates of the objects being analyzed using calibrated pairs of optical-electronic sensors. The results of image analysis from each of the optoelectronic sensors are used to accompany moving objects and analyze their motion paths in the working scene space. To implement the developed theoretical approaches, a modular optoelectronic device has been developed, consisting of two types of modules. The first type of module is a standalone opto-electronic module, which includes an opto-electronic sensor and means for processing and extracting primary features immediately upon receiving images for their subsequent analysis. The second type is a computational module that provides processing of primary data from a set of modules of the first type. Data transfer between device modules is provided via radio over a WiFi network. A distinctive feature of the developed device is the primary processing of images immediately upon their receipt and transmission over the radio channel of a small amount of data about the selected objects to the computing module, which performs the final stages of data processing and generates a set of parameters describing the characteristics and spatial coordinates of the objects found on the working scene for their further of use. Experimental studies were conducted on the developed simulation model, which confirmed the correctness of the developed theoretical approach and the possibility of its application in practice.

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Li, Leiming, Wenyao Zhu, and Hongwei Hu. "Multivisual Animation Character 3D Model Design Method Based on VR Technology." Complexity 2021 (April 20, 2021): 1–12. http://dx.doi.org/10.1155/2021/9988803.

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For VR systems, one of its core parts is to present people with a real and immersive 3D simulation environment. This paper uses real-time computer graphics technology, three-dimensional modeling technology, and binocular stereo vision technology to study the multivisual animation character objects in virtual reality technology; designs a binocular stereo vision animation system; designs and produces a three-dimensional model; and develops a virtual multivisual animation scene application. The main research content and work performed in the text include the research of the basic graphics rendering pipeline process and the analysis and research of each stage of the rendering pipeline. It mainly analyzes the 3D graphics algorithm used in the three-dimensional geometric transformation of computer graphics and studies the basic texture technology, basic lighting model, and other image output processes used in the fragment processing stage. Combined with the development needs of the subject, the principles of 3D animation rendering production software and 3D graphics modeling are studied, and the solid 3D model displayed in the virtual reality scene is designed and produced. This article also reflects the application of virtual reality in multivisual animation character design from the side, so it has realistic value and application prospects.

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Huang Peng, Qizi, Tianyu Liu, Quan Sun, and Wenwei Huang. "Reliability estimation for aluminum alloy welded joint with automatic image measurement of surface crack growth." Engineering Computations 33, no. 4 (2016): 1205–23. http://dx.doi.org/10.1108/ec-04-2015-0092.

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Purpose – As an important connecting component, the reliability of aluminium alloy welded joints influences the whole structural effectiveness and stability of equipment. The purpose of this paper is to propose a novel reliability estimation approach to the welded joints based on time-transformed Wiener process with automatic image measurement of crack growth. The crack length information of the welded joints is incorporated into reliability analysis to reflect the product time-varying characteristics. Design/methodology/approach – The proposed approach is superior to other crack growth estimations in that it innovatively introduce a non-contact and flexible photogrammetry technique.First, on-line crack growth images of aluminium alloy welded joints are acquired by the designed monitor system. Second, crack length is calculated with image measurement, then the crack growth data during the manufacturing process is prepared. Finally, a time-transformed Wiener process is used to modeling the degradation, and reliability estimation is carried out with Wiener model. The approach has been validated on five 7075-T7351 welded joint samples. Findings – The method has a twofold task: first, the extraction of crack length growth data by a sequence of image processing. The main step is to model the crack skeleton with crack skeleton tree, and remove it edges to calculate the length of crack; second, the prediction of crack growth and reliability estimation. Research limitations/implications – The limitation of proposed method should not be ignored. The pixel/mm scale should be calibrated in advance that means once we have built the monitor system, the relative position of the CCD camera and the surveyed crack cannot change anymore. It has reduced the flexibility. To improve this, we can obtain binocular vision in crack image measurement. The 3-D measurements could solve calibration problem and provide more information, such as the depth and the orientation of crack to research. Therefore, future work can be centered on the improvement of monitor system and measurement precision. Originality/value – In the paper a novel method to estimate reliability of crack growth from welded joint based on image measurement has been presented. This method could be widely applied in different filed of manufacturing systems, reliability engineering and structural analysis.

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Wang, Ting Ting. "Image Processing Based on Three-Dimensional Stereo Vision." Applied Mechanics and Materials 556-562 (May 2014): 5017–20. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.5017.

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Three-dimensional stereo vision technology has the capability of overcoming drawbacks influencing by light, posture and occluder. A novel image processing method is proposed based on three-dimensional stereoscopic vision, which optimizes model on the basis of camera binocular vision and in improvement of adding constraints to traditional model, moreover ensures accuracy of later location and recognition. To verify validity of the proposed method, firstly marking experiments are conducted to achieve fruit location, with the result of average error rate of 0.65%; and then centroid feature experiments are achieved with error from 5.77mm to 68.15mm and reference error rate from 1.44% to 5.68%, average error rate of 3.76% while the distance changes from 300mm to 1200mm. All these data of experiments demonstrate that proposed method meets the requirements of three-dimensional imageprocessing.

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12

Dijkstra, T. "Image processing, analysis and machine vision." Neurocomputing 6, no. 3 (1994): 378–79. http://dx.doi.org/10.1016/0925-2312(94)90073-6.

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13

Saarinen, Kari. "Image processing, analysis and machine vision." Signal Processing 35, no. 1 (1994): 102–4. http://dx.doi.org/10.1016/0165-1684(94)90202-x.

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14

Liu, Hai Bo, Su Yan Zhang, and Yu Mei Wang. "Mechanical Robot Vision Image Segmentation Using Chaos-Particle Swarm Optimization Algorithm." Applied Mechanics and Materials 574 (July 2014): 511–16. http://dx.doi.org/10.4028/www.scientific.net/amm.574.511.

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The image segmentation of a robot binocular stereo vision system is the key issue in imaging processing. In this paper, the method of 2-D maximum entropy threshold image segmentation with chaos-particle swarm optimization algorithm is used to segment the images information collected by a robot vision system, and the algorithm is checked by a real robot binocular stereo vision system. The results show that more space information of an image is sufficiently used by the above method, and the running time is shortened by the algorithm. In addition, the image segmentation effect is better than other conventional methods.

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Li, Chang Chun, Tian Hou Zhang, Hua Guan Liu, Jing Yu, and Shi Feng Wang. "Study on Material Stacking Image Based on Machine Vision." Key Engineering Materials 460-461 (January 2011): 178–83. http://dx.doi.org/10.4028/www.scientific.net/kem.460-461.178.

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Combining materials handling and stacking operations, this paper takes the fertilizer bags as the object and studies on the image processing method of the material stacking and segments the stacking image. Using binocular vision technology generates stacking depth image, and the depth data is extracted. It can provide a theoretical basis for the robot to realize the automatic recognition of material stacking.

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Shen, Jie, Hong Ye Sun, Hui Bin Wang, Zhe Chen, and Yi Wei. "A Binocular Vision System for Underwater Target Detection." Applied Mechanics and Materials 347-350 (August 2013): 883–90. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.883.

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For the underwater target detecting task, a binocular vision system specialized to the underwater optical environment is proposed. The hardware platform is comprised of a image acquising unit, a image processing unit and a upper computer. Accordingly, the loaded software system is operated for the camera calibration, image preprocessing, feature point extraction, stereo matching and the three-dimensional restoration. The improved Harris operator is introduced for the three-dimensional reconstruction, considering the high scattering and strong attenuation by the underwater optical environment. The experiment results prove that the improved Harris operator is better adapt to the complex underwater optical environment and the whole system has the ability to obtain the three-dimensional coordinate of the underwater target more efficient and accurate.

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17

Gawande, Mohini. "Image Detection System Using Image Processing." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 5356–62. http://dx.doi.org/10.22214/ijraset.2021.36190.

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The increasing popularity of Social Networks makes change the way people interact. These interactions produce a huge amount of data and it opens the door to new strategies and marketing analysis. According to Instagram and Tumblr, an average of 80 and 59 million photos respectively are published every day, and those pictures contain several implicit or explicit brand logos. Image recognition is one of the most important fields of image processing and computer vision. The CNNs are a very effective class of neural networks that is highly effective at the task of image classifying, object detection and other computer vision problems.in recent years, several scale- invariant features have been proposed in literature, this paper analyzes the usage of Speeded Up Robust Features (SURF) as local descriptors, and as we will see, they are not only scale-invariant features, but they also offer the advantage of being computed very efﬁciently. Furthermore, a fundamental matrix estimation method based on the RANSAC is applied.

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Wang, Zhen Li, Shou Yin Lu, and Jian Li. "Vision Servo System for High-Voltage-Live-Working Robot." Advanced Materials Research 706-708 (June 2013): 1108–11. http://dx.doi.org/10.4028/www.scientific.net/amr.706-708.1108.

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This paper presents a vision servo system for high-voltage-live-working robot, which consists of image acquisition subsystem, image processing subsystem and robot control subsystem. It uses binocular stereo camera which mounted on the hand of robot to get the image of the working scene, and then uses binocular stereo vision algorithms together with target tracking algorithm to get the 3-Dimensions information of the power equipment. The robot control subsystem receives the 3-Dimensions information, and then guide the robot moving to the target location to implement the high-voltage-work. The proposed system can implement the high-voltage-work without Human involvement and improve works level of automation and efficiency.

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Hou, A. Lin, Juan Chen, Zhi Juan Jin, Qing Liao, and Ying Geng. "Binocular Vision Measurement of Distance Based on Vehicle Logo Location." Applied Mechanics and Materials 229-231 (November 2012): 1154–57. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1154.

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A measuring system of vehicle distance is proposed on the basis of binocular vision using location information of the vehicle logo. The spatial location of the target vehicle can be obtained by the pixel coordinates in the image plane due to the logo is sited at the central axis of the vehicle. The camera calibration algorithm is accomplished by conversion relation matrix between the world coordinate system and the image coordinate. And then the binocular logo image pairs are matched. Finally, the distance of the target vehicle is calculated. The simulation experiments have been done and the results show that the proposed method of distance measurement has better performance with rapid processing and higher accuracy.

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Zhang, Jing, Ming Zhong, and Bo Huang. "A Monocular Vision System Based on the Equidistance Pseudo Binocular Feature Recognition." Applied Mechanics and Materials 226-228 (November 2012): 1987–92. http://dx.doi.org/10.4028/www.scientific.net/amm.226-228.1987.

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Monocular vision system for medical robot must have high accuracy. In traditional monocular vision system, localization algorithm is realized by image space transformation, which leads to a trivial calculation process and a complex camera calibration method, therefore, this paper presents a new target characteristics identification method. Through the establishment of an equidistance pseudo binocular image acquisition way, searching the image and space coordinate transformation relation, avoid the complicated space matrix conversion and improve the position precision. Using Pointer method for image processing and customized backtracking boundary conditions for image searching, this paper realizes the curve fitting of target features boundary, and pattern recognition. Finally, an experiment is completed to guide the pharmacy movement of the Staubli TX40 arm, whose software runs within 200 ms and location error is less in 0.2 mm, verifies the validity of the algorithm.

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Atkočiūnas, E., R. Blake, A. Juozapavičius, and M. Kazimianec. "Image Processing in Road Traffic Analysis." Nonlinear Analysis: Modelling and Control 10, no. 4 (2005): 315–32. http://dx.doi.org/10.15388/na.2005.10.4.15112.

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The article presents an application of computer vision methods to traffic flow monitoring and road traffic analysis. The application is utilizing image-processing and pattern recognition methods designed and modified to the needs and constrains of road traffic analysis. These methods combined together gives functional capabilities of the system to monitor the road, to initiate automated vehicle tracking, to measure the speed, and to recognize number plates of a car. Software developed was applied in and approved with video monitoring system, based on standard CCTV cameras connected to wide area network computers.

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Wang, Xin Jie, Zhi Lin Yang, and Jie Liu. "The Location of Quadruped Robot with Hand-Fused-Foot Based on Binocular Vision." Advanced Materials Research 694-697 (May 2013): 1925–30. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.1925.

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Robot location is a key technology of quadruped robot with Hand-fused-Foot. The location method based on binocular vision system is studied for quadruped robot with Hand-fused-Foot. After obtaining image by a single camera, the object is segmented by using characteristic extraction method based on color characteristic. Then image processing such as filtering (de-noising) and opening is performed. The object is identified and its centroid coordinate in image is obtained. Location of robot based on environment reference--object coordinate is achieved. Experiments show the effectiveness and the accuracy (within 4cm) of the method.

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Rosenfeld, A. "Image Analysis and Computer Vision: 1992." Computer Vision and Image Understanding 58, no. 1 (1993): 85–135. http://dx.doi.org/10.1006/cviu.1993.1034.

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Rosenfeld, A. "Image Analysis and Computer Vision: 1993." Computer Vision and Image Understanding 59, no. 3 (1994): 367–404. http://dx.doi.org/10.1006/cviu.1994.1030.

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Rosenfeld, Azriel. "Image Analysis and Computer Vision: 1994." Computer Vision and Image Understanding 62, no. 1 (1995): 90–143. http://dx.doi.org/10.1006/cviu.1995.1044.

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Rosenfeld, Azriel. "Image Analysis and Computer Vision: 1995." Computer Vision and Image Understanding 63, no. 3 (1996): 568–612. http://dx.doi.org/10.1006/cviu.1996.0041.

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Rosenfeld, Azriel. "Image Analysis and Computer Vision: 1996." Computer Vision and Image Understanding 66, no. 1 (1997): 33–93. http://dx.doi.org/10.1006/cviu.1997.0602.

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Rosenfeld, Azriel. "Image Analysis and Computer Vision: 1997." Computer Vision and Image Understanding 70, no. 2 (1998): 239–84. http://dx.doi.org/10.1006/cviu.1998.0697.

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Rosenfeld, Azriel. "Image Analysis and Computer Vision: 1998." Computer Vision and Image Understanding 74, no. 1 (1999): 36–95. http://dx.doi.org/10.1006/cviu.1999.0746.

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Rosenfeld, Azriel. "Image Analysis and Computer Vision: 1999." Computer Vision and Image Understanding 78, no. 2 (2000): 222–302. http://dx.doi.org/10.1006/cviu.2000.0835.

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Dong, Chen, and Shu Guang Dai. "Design of Program Framework of Binocular Vision Measurement System Based on DM642." Applied Mechanics and Materials 220-223 (November 2012): 1311–14. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.1311.

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As the rapid progress and development of DSP technology, a new way to solve the video signal processing was accepted. At present, binocular measurement instrument are mostly based on image capture card and PC on the market, expensive and bulky. For this problem, binocular vision measurement system based on DSP has been used. The design of elementary program structure about video processing which based on DSP/BIOS was finished and verified for its real-time. The results of the experiment show that the driver can be well used in the system.

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Zhou, Wujie, Lu Yu, Weiwei Qiu, Ting Luo, Zhongpeng Wang, and Ming-Wei Wu. "Utilizing binocular vision to facilitate completely blind 3D image quality measurement." Signal Processing 129 (December 2016): 130–36. http://dx.doi.org/10.1016/j.sigpro.2016.06.005.

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Huo, Jiaofei, and Xiaomo Yu. "Three-dimensional mechanical parts reconstruction technology based on two-dimensional image." International Journal of Advanced Robotic Systems 17, no. 2 (2020): 172988142091000. http://dx.doi.org/10.1177/1729881420910008.

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With the development of computer technology and three-dimensional reconstruction technology, three-dimensional reconstruction based on visual images has become one of the research hotspots in computer graphics. Three-dimensional reconstruction based on visual image can be divided into three-dimensional reconstruction based on single photo and video. As an indirect three-dimensional modeling technology, this method is widely used in the fields of film and television production, cultural relics restoration, mechanical manufacturing, and medical health. This article studies and designs a stereo vision system based on two-dimensional image modeling technology. The system can be divided into image processing, camera calibration, stereo matching, three-dimensional point reconstruction, and model reconstruction. In the part of image processing, common image processing methods, feature point extraction algorithm, and edge extraction algorithm are studied. On this basis, interactive local corner extraction algorithm and interactive local edge detection algorithm are proposed. It is found that the Harris algorithm can effectively remove the features of less information and easy to generate clustering phenomenon. At the same time, the method of limit constraints is used to match the feature points extracted from the image. This method has high matching accuracy and short time. The experimental research has achieved good matching results. Using the platform of binocular stereo vision system, each step in the process of three-dimensional reconstruction has achieved high accuracy, thus achieving the three-dimensional reconstruction of the target object. Finally, based on the research of three-dimensional reconstruction of mechanical parts and the designed binocular stereo vision system platform, the experimental results of edge detection, camera calibration, stereo matching, and three-dimensional model reconstruction in the process of three-dimensional reconstruction are obtained, and the full text is summarized, analyzed, and prospected.

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Song, Wei, Yan Xiao Chen, Long Ji Zhang, and Shu Yuan Qin. "Design of Automatic Tracking System Based on FPGA and Binocular Vision." Applied Mechanics and Materials 397-400 (September 2013): 1469–72. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.1469.

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An intelligent system with automatic tracking function based on FPGA and binocular vision was designed. The system can be divided into five parts, and they are the image acquisition and processing module, moving target detection module, motion control module, moving target tracking module, and the depth information computing module. The basic design theory and the structure of each component were analyzed from software and hardware.

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Amini, Amir A., Fred L. Bookstein, and David C. Wilson. "Biomedical Image Analysis." Computer Vision and Image Understanding 66, no. 2 (1997): 95–96. http://dx.doi.org/10.1006/cviu.1997.0616.

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LIONS, PIERRE-LOUIS. "AXIOMATIC DERIVATION OF IMAGE PROCESSING MODELS." Mathematical Models and Methods in Applied Sciences 04, no. 04 (1994): 467–75. http://dx.doi.org/10.1142/s0218202594000261.

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We briefly review the derivation due to Alvarez, Guichard, Morel and the author of mathematical models in Image Processing. We deduce from classical axions in Computer Vision some nonlinear partial differential equations of evolution type that correspond to general multi-scale analysis (scale-space). We also obtain specific nonlinear models that satisfy additional invariances which are relevant for the analysis of images.

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Wang, Xinhua, Dayu Li, and Guang Zhang. "Panoramic Stereo Imaging of a Bionic Compound-Eye Based on Binocular Vision." Sensors 21, no. 6 (2021): 1944. http://dx.doi.org/10.3390/s21061944.

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With the rapid development of the virtual reality industry, one of the bottlenecks is the scarcity of video resources. How to capture high-definition panoramic video with depth information and real-time stereo display has become a key technical problem to be solved. In this paper, the optical optimization design scheme of panoramic imaging based on binocular stereo vision is proposed. Combined with the real-time processing algorithm of multi detector mosaic panoramic stereo imaging image, a panoramic stereo real-time imaging system is developed. Firstly, the optical optimization design scheme of panoramic imaging based on binocular stereo vision is proposed, and the space coordinate calibration platform of ultra-high precision panoramic camera based on theodolite angle compensation function is constructed. The projection matrix of adjacent cameras is obtained by solving the imaging principle of binocular stereo vision. Then, a real-time registration algorithm of multi-detector mosaic image and Lucas-Kanade optical flow method based on image segmentation are proposed to realize stereo matching and depth information estimation of panoramic imaging, and the estimation results are analyzed effectively. Experimental results show that the stereo matching time of panoramic imaging is 30 ms, the registration accuracy is 0.1 pixel, the edge information of depth map is clearer, and it can meet the imaging requirements of different lighting conditions.

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Sanfeliu, A., R. Alquézar, J. Andrade, J. Climent, F. Serratosa, and J. Vergés. "Graph-based representations and techniques for image processing and image analysis." Pattern Recognition 35, no. 3 (2002): 639–50. http://dx.doi.org/10.1016/s0031-3203(01)00066-8.

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Yang, Jiachen, Huifang Xu, Yang Zhao, Hehan Liu, and Wen Lu. "Stereoscopic image quality assessment combining statistical features and binocular theory." Pattern Recognition Letters 127 (November 2019): 48–55. http://dx.doi.org/10.1016/j.patrec.2018.10.012.

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Gurevich, Igor, and Vera Yashina. "Descriptive Image Analysis. Foundations and Descriptive Image Algebras." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 11 (2019): 1940018. http://dx.doi.org/10.1142/s0218001419400184.

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The paper is devoted to Descriptive Image Analysis (DA) — a leading line of the modern mathematical theory of image analysis. DA is a logically organized set of descriptive methods, mathematical objects, and models and representations aimed at analyzing and evaluating the information represented in the form of images, as well as for automating the extraction from images of knowledge and data needed for intelligent decision-making. The basic idea of DA consists of embedding all processes of analysis (processing, recognition, understanding) of images into an image formalization space and reducing it to (1) construction of models/representations/formalized descriptions of images; (2) construction of models/representations/formalized descriptions of transformations over models and representations of images. We briefly discuss the basic ideas, methodological principles, mathematical methods, objects, and components of DA and the basic results determining the current state of the art in the field. Image algebras (IA) are considered in the context of a unified language for describing mathematical objects and operations used in image analysis (the standard IA by Ritter and the descriptive IA by Gurevich).

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Yang, Yuxiang, Xiang Meng, and Mingyu Gao. "Vision System of Mobile Robot Combining Binocular and Depth Cameras." Journal of Sensors 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/4562934.

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In order to optimize the three-dimensional (3D) reconstruction and obtain more precise actual distances of the object, a 3D reconstruction system combining binocular and depth cameras is proposed in this paper. The whole system consists of two identical color cameras, a TOF depth camera, an image processing host, a mobile robot control host, and a mobile robot. Because of structural constraints, the resolution of TOF depth camera is very low, which difficultly meets the requirement of trajectory planning. The resolution of binocular stereo cameras can be very high, but the effect of stereo matching is not ideal for low-texture scenes. Hence binocular stereo cameras also difficultly meet the requirements of high accuracy. In this paper, the proposed system integrates depth camera and stereo matching to improve the precision of the 3D reconstruction. Moreover, a double threads processing method is applied to improve the efficiency of the system. The experimental results show that the system can effectively improve the accuracy of 3D reconstruction, identify the distance from the camera accurately, and achieve the strategy of trajectory planning.

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Zhang, Ben, and Denglin Zhu. "Improved Camera Calibration Method and Accuracy Analysis for Binocular Vision." International Journal of Pattern Recognition and Artificial Intelligence 35, no. 09 (2021): 2155010. http://dx.doi.org/10.1142/s0218001421550107.

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The quality of the stereo camera calibration method governs the accuracy of the binocular vision and thus determines the precision of the 3D reconstruction. Spurred by that, in this paper, we propose an improved calibration method that increases the calibration accuracy by optimizing the captured corners. Our method is multi-staged, where first, we employ the Harris corner detector to identify the uncertainties of all image corners. Then, for each detected corner, we apply a linear optimization, and finally, we calibrate the intrinsic and extrinsic parameters of the binocular vision setup by employing a nonlinear optimization scheme. We confirm the validity of our technique by analyzing the factors influencing the camera calibration accuracy and confirm the experimental conditions. Ultimately, we evaluate the proposed method and demonstrate that the mean error of our binocular vision architecture is more appealing compared to current literature.

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Wiley, Victor, and Thomas Lucas. "Computer Vision and Image Processing: A Paper Review." International Journal of Artificial Intelligence Research 2, no. 1 (2018): 22. http://dx.doi.org/10.29099/ijair.v2i1.42.

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Computer vision has been studied from many persective. It expands from raw data recording into techniques and ideas combining digital image processing, pattern recognition, machine learning and computer graphics. The wide usage has attracted many scholars to integrate with many disciplines and fields. This paper provide a survey of the recent technologies and theoretical concept explaining the development of computer vision especially related to image processing using different areas of their field application. Computer vision helps scholars to analyze images and video to obtain necessary information, understand information on events or descriptions, and scenic pattern. It used method of multi-range application domain with massive data analysis. This paper provides contribution of recent development on reviews related to computer vision, image processing, and their related studies. We categorized the computer vision mainstream into four group e.g., image processing, object recognition, and machine learning. We also provide brief explanation on the up-to-date information about the techniques and their performance.

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Iskra, N. A. "APPROACH TO IMAGE ANALYSIS FOR COMPUTER VISION SYSTEMS." Doklady BGUIR 18, no. 2 (2020): 62–70. http://dx.doi.org/10.35596/1729-7648-2020-18-2-62-70.

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This paper suggests an approach to the semantic image analysis for application in computer vision systems. The aim of the work is to develop a method for automatically construction of a semantic model, that formalizes the spatial relationships between objects in the image and research thereof. A distinctive feature of this model is the detection of salient objects, due to which the construction algorithm analyzes significantly less relations between objects, which can greatly reduce the image processing time and the amount of resources spent for processing. Attention is paid to the selection of a neural network algorithm for object detection in an image, as a preliminary stage of model construction. Experiments were conducted on test datasets provided by Visual Genome database, developed by researchers from Stanford University to evaluate object detection algorithms, image captioning models, and other relevant image analysis tasks. When assessing the performance of the model, the accuracy of spatial relations recognition was evaluated. Further, the experiments on resulting model interpretation were conducted, namely image annotation, i.e. generating a textual description of the image content. The experimental results were compared with similar results obtained by means of the algorithm based on neural networks algorithm on the same dataset by other researchers, as well as by the author of this paper earlier. Up to 60 % improvement in image captioning quality (according to the METEOR metric) compared with neural network methods has been shown. In addition, the use of this model allows partial cleansing and normalization of data for training neural network architectures, which are widely used in image analysis among others. The prospects of using this technique in situational monitoring are considered. The disadvantages of this approach are some simplifications in the construction of the model, which will be taken into account in the further development of the model.

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Xie, Yong Gang, Zhong Min Wang, and Shi Tao Su. "The Research of Binocular Ranging System on Independent Mobile Robot." Advanced Materials Research 462 (February 2012): 603–8. http://dx.doi.org/10.4028/www.scientific.net/amr.462.603.

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Timeliness and accuracy is a key to be resolved on robot binocular measurement. In this paper, a kind of robot vision projection has been completely established. It analyzes the principle of binocular ranging in three aspects, makes the calculation concise and easy to understand, and expands the range of effective distance. On binocular image processing, we have proposed a gray-scale computing for, firstly, generating characteristic area, then, executing template matching in the area, finally, extracting feature points and matching them in the templates. It ensures certain robustness to noise spots and tries its best to avoid mismatches. The experiments show that the robot vision system has a better accuracy and a low time complexity, and the robot can react in real time.

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Rakhimov, Bakhtiyar Saidovich, Feroza Bakhtiyarovna Rakhimova, Sabokhat Kabulovna Sobirova, Furkat Odilbekovich Kuryazov, and Dilnoza Boltabaevna Abdirimova. "Review And Analysis Of Computer Vision Algorithms." American Journal of Applied sciences 03, no. 05 (2021): 245–50. http://dx.doi.org/10.37547/tajas/volume03issue05-39.

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Computer vision as a scientific discipline refers to the theories and technologies for creating artificial systems that receive information from an image. Despite the fact that this discipline is quite young, its results have penetrated almost all areas of life. Computer vision is closely related to other practical fields like image processing, the input of which is two-dimensional images obtained from a camera or artificially created. This form of image transformation is aimed at noise suppression, filtering, color correction and image analysis, which allows you to directly obtain specific information from the processed image. This information may include searching for objects, keypoints, segments, and annexes;

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Jian, Muwei, Xiangyu Liu, Hanjiang Luo, Xiangwei Lu, Hui Yu, and Junyu Dong. "Underwater image processing and analysis: A review." Signal Processing: Image Communication 91 (February 2021): 116088. http://dx.doi.org/10.1016/j.image.2020.116088.

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Liu, Zhi-Qiang. "Bayesian Paradigms in Image Processing." International Journal of Pattern Recognition and Artificial Intelligence 11, no. 01 (1997): 3–33. http://dx.doi.org/10.1142/s0218001497000020.

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A large number of image and spatial information processing problems involves the estimation of the intrinsic image information from observed images, for instance, image restoration, image registration, image partition, depth estimation, shape reconstruction and motion estimation. These are inverse problems and generally ill-posed. Such estimation problems can be readily formulated by Bayesian models which infer the desired image information from the measured data. Bayesian paradigms have played a very important role in spatial data analysis for over three decades and have found many successful applications. In this paper, we discuss several aspects of Bayesian paradigms: uncertainty present in the observed image, prior distribution modeling, Bayesian-based estimation techniques in image processing, particularly, the maximum a posteriori estimator and the Kalman filtering theory, robustness, and Markov random fields and applications.

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Abdulhamid, Mohanad, and Lwanga Wanjira. "Image Processing Techniques Based Crowd Size Estimation." Radioelectronics. Nanosystems. Information Technologies 12, no. 3 (2020): 407–14. http://dx.doi.org/10.17725/rensit.2020.12.407.

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Image processing algorithms are the basis for image computer analysis and machine Vision. Employing a theoretical foundation, image algebra, and powerful development tools, Visual C++, Visual Fortran, Visual Basic, and Visual Java, high-level and efficient computer vision techniques have been developed. This paper analyzes different image processing algorithms by classifying them in logical groups. In addition, specific methods are presented illustrating the application of such techniques to the real world images. In most cases more than one method is used. This allows a basis for comparison of different methods as advantageous features as well as negative characteristics of each technique is delineated. The main objective of this paper is to use image processing techniques to estimate the size of a crowd from a still photograph. The simulation results show that the different images have different efficiencies.

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Zhang, Jie. "Design of Intelligent Aim System of Tear Bomb Emitter Based on Binocular Stereo Vision." Applied Mechanics and Materials 130-134 (October 2011): 3505–10. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.3505.

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The intelligent Aim system of the Tear Bomb Emitter based on binocular stereo vision has been designed for the armored car equipped in our Armed Police Force. In this paper, according to the intrinsical feature of the background, the binocular stereo vision is chose to detect the forward distance between the bomb emitter and the crowd which the emitter needs to aim at. A new way which is based on integrating temporal information with spatial information has been presented. Then the forward distance was obtained according to the camera calibration, image processing, and error model. The error and measuring experiment shows that the percentage error is less than 2% and this method is feasible and effective.

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