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Technical framework of energy-saving construction management of intelligent building based on computer vision algorithm

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SOFT COMPUTING 2023年 1-10页

作者： Ma, Weini Henan Inst Econ & Trade Engn Fac Econ Zhengzhou 450000 Henan Peoples R China

At present, China's urbanization transformation is accelerating, the construction industry is developing rapidly, and people's requirements for buildings are also increasing, which leads to the increasing energy consumption. Therefore, energy-saving construction in the construction industry is imminent. During the actual life cycle of a building project, including planning, design, construction and later operation and maintenance, energy consumption will be generated in the above processes. Based on this background, this research realized the design of intelligent building management and information system for energy conservation projects by introducing computer vision algorithm. The system is integrated with laws and regulations, economic benefits, technical steps, quality management, cost management, schedule management and other modules. The design process is relatively complex. Therefore, this work adopts modern computer vision algorithm technology and uses relevant tools to collect, store, and analyze a large amount of information in each stage of energy-saving project management process and realize information management from project approval, design, drawing review, and construction to acceptance. Finally, this paper builds system interface layer, system function layer, and database support layer. The system measurement shows that the building energy consumption can be predicted easily, accurately and stably by inputting the energy consumption data collected by each part of the target building. The system realizes the combination of qualitative and quantitative research on energy conservation regulation and improves the informatization level of China's energy conservation research and construction. This paper designs a kind of intelligent building energy-saving management system by studying computer vision algorithm.

关键词： Computer vision algorithm Intelligent building Energy-saving construction

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Positioning measurement using a new artificial vision algorithm in LabVIEW based on the analysis of images on an LCD screen

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2020年第1-2期109卷 155-170页

作者： de Francisco Ortiz, Oscar Estrems Amestoy, Manuel Carrero-Blanco, Julio MDE UPCT Engn & Appl Tech Dept San Javier Air Force Base Univ Ctr Def C Coronel Lopez Pena S-N Murcia 30720 Spain Polytech Univ Cartagena Dept Mat & Mfg Engn Cartagena 30202 Spain

Research in vision systems applied to manufacturing processes has increased during the last years. Nevertheless, accurate positioning systems frequently require costly investments. This article presents a new algorithm developed in LabVIEW for controlling a novel positioning system that processes images to obtain the position, which could be implemented in micromachining. With this aim, the method uses the analysis of the LEDs shown in an image projected on an LCD screen to perform an accurate positioning. The ultimate goal of this method is to get the coordinates of the images shown on the screen in order to know the movement made by the system and, in this way, be able to compensate the error. The experimental results and related analysis developed proved the accuracy and consistency in dissimilar situations. In addition, once implemented the algorithm proposed in a closed loop program, a positioning system is achieved where the error is always convergent.

关键词： Image processing Positioning control vision algorithm Precision engineering Micromachining LabVIEW

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Development and Evaluation of a vision algorithm for 3D Reconstruction of Novel Objects from Three Camera Views

Development and Evaluation of a Vision Algorithm for 3D Reco...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Colbert, Steven C. Alqasemi, Redwan Dubey, Rajiv V. Franz, Gregor Woellhaf, Konrad Univ S Florida Dept Mech Engn Tampa FL 33620 USA Univ Appl Sci Ravensburg Weingarten Weingarten Germany

ISBN: (纸本)9781424466757

When planning robotic grasping and manipulation maneuvers, knowledge of the shape and pose of the object of interest is critical information. In order for an autonomous or semi-autonomous system to operate intelligently in an unstructured environment and interact with novel objects, it must have the ability to recover this information at run time, even when no a priori information of the object is available. In this paper, we describe the development and testing of an algorithm that can reconstruct the full 3D geometry of a novel object from just three images. A variant of shape from silhouettes, the algorithm first generates a rough surface approximation in the form of a point cloud. This approximation is then refined by fitting an eleven parameter geometric surface to the points in such a manner that the surface ignores noise and perspective projection shadows. We test the algorithm in both simulation and on several real world objects. We show that the algorithm provides accurate reconstructions that can be directly used to plan grasping maneuvers. Compared to other attempts in the literature, the proposed algorithm is faster, requires fewer images, is more accurate, and degrades gracefully in the presence of bad data. A real world test case is included that shows that the algorithm still yields usable results when the form of the object is amorphous or otherwise non-geometric.

关键词： 3D object reconstruction approximation theory autonomous system camera view cameras grippers image reconstruction image reconstruction manipulation maneuvering pose estimation robot vision robotic grasp planning rough surface approximation rough surfaces semiautonomous system solid modelling vision algorithm

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Robust Iris Recognition Framework Using Computer vision algorithms 4

Robust Iris Recognition Framework Using Computer Vision Algo...

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4th International Conference on Smart Grid and Smart Cities (ICSGSC)

作者： Hussein, Nashwan Jasim Al Furat Al Awsat Tech Univ Tech Coll Management Najaf Iraq

ISBN: (纸本)9781728194042

Nowadays under human observations iris recognition is playing an essential role, it observed that there are some points are very essential for this method like accuracy, efficiency & processing time. There are several problems has been recorded for this kind of technique. Under previous researches, many concepts have been reported for iris-based segmentation, classification & feature extraction techniques. This research dealt with implementing a novel framework of robust iris segmentation utilizing computer vision technique, FFNN classifier & hybrid feature extraction technique. For the non-iris images method of the novel iris, segmentation has been proposed in this paper. The technique of novel iris segmentation based on 2 methods regards pupil segmentation, after that fusion of enhancing & shrinking visible contour has been framed for segmentation of iris through collaborating novel burden forcing for visible contour model. Moreover, then UN wrapped iris segmentation performed well with the technique of normalization non-circular iris. Whatever, for better iris segmentation research, utilized a proposed method of feature extraction under Discrete Wavelet Transform, letter utilized geometric & texture features of the segmented image. Achieved features have collaborated through a vector of a hybrid feature. For the reason of recognition, we are utilizing a vision algorithm with an FFNN classifier. This paper focused on the concepts related to a robust iris recognition framework using a vision algorithm. Daugman demodulates the yield of the Gabor channels to pack the information. It separates the stage data into four levels and for every conceivable quadrant in-plane to get a minimal 256-byte layout, which takes into consideration proficient capacity and correlation of irises. Experimental outputs have been described as the proposed robust iris segmentation method adopted greater accuracy on the challenging segmentation algorithm thousand databases.

关键词： Iris recognition segmentation algorithm vision algorithm robust segmentation vision computer method

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Nonlinear Coordinated Steering and Braking Control of vision-Based Autonomous Vehicles in Emergency Obstacle Avoidance

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2016年第11期17卷 3230-3240页

作者： Guo, Jinghua Hu, Ping Wang, Rongben Xiamen Univ Dept Mech & Elect Engn Xiamen 361005 Peoples R China Dalian Univ Technol Sch Autonomous Engn Dalian 116024 Peoples R China Jilin Univ Coll Traff Changchun 130012 Peoples R China

This paper discusses dynamic control design for automated driving of vision-based autonomous vehicles, with a special focus on the coordinated steering and braking control in emergency obstacle avoidance. An autonomous vehicle is a complex multi-input and multi-output (MIMO) system, which possesses the features of parameter uncertainties and strong nonlinearities, and the coupled phenomena of longitudinal and lateral dynamics are evident in a combined cornering and braking maneuver. In this work, an effective coordinated control system for automated driving is proposed to deal with these coupled and nonlinear features and reject the disturbances. First, a vision algorithm is constructed to detect the reference path and provide the local location information between vehicles and reference path in real time. Then, a novel coordinated steering and braking control strategy is proposed based on the nonlinear backstepping control theory and the adaptive fuzzy sliding-mode control technique, and the asymptotic convergence of the proposed coordinated control system is proven by the Lyapunov theory. Finally, experimental tests manifest that the proposed control strategy possesses favorable tracking performance and enhances the riding comfort and stability of autonomous vehicles.

关键词： Autonomous vehicles nonlinear coordinated control vision algorithm fuzzy sliding mode control steering and braking control

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Make complex CAPTCHAs simple: A fast text captcha solver based on a small number of samples

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INFORMATION SCIENCES 2021年 578卷 181-194页

作者： Wang, Yao Wei, Yuliang Zhang, Mingjin Liu, Yang Wang, Bailing Harbin Inst Technol Sch Comp Sci & Technol Weihai 264209 Peoples R China Harbin Inst Technol Res Inst Cyberspace Secur Harbin 150001 Peoples R China

Text-based captchas are still widely used by many websites such as Wikipedia and Microsoft despite the emergence of many alternative captchas. Recently, the design of text-based captchas has become more and more complex to resist attacks from automatic cracking programs. However, most of the existing captcha solving methods have certain shortcomings, such as insufficient accuracy, poor generalization performance, and the need for a large number of labeled samples. This study proposes a fast captcha solver that can effectively break text-based captchas with complex security features using a small amount of labeled data. The solver was achieved by constructing a captcha transformation model based on generative adversarial networks to simplify the captcha images before character segmentation and recognition. Results showed that the proposed captcha solver achieved a high success rate of over 96% character accuracy and 74% captcha accuracy for all evaluated schemes. Moreover, the average time to process a single captcha image using a laptop GPU was only 4-8 ms. The effectiveness of this work may encourage captcha designers to reconsider a more secure human-machine distinction mechanism. (c) 2021 Elsevier Inc. All rights reserved.

关键词： Text CAPTCHAs Deep learning Generative adversarial networks vision algorithm

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PARALLEL COORDINATION OF IMAGE OPERATORS - MODEL, algorithm AND PERFORMANCE

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IMAGE AND vision COMPUTING 1993年第3期11卷 129-138页

作者： HWANG, SY TANIMOTO, SL UNIV WASHINGTON DEPT COMP SCI & ENGNSEATTLEWA 98195

To obtain machine vision algorithms which are robust in the face of variations in image lighting, arrangements of objects, viewing parameters, etc., it is helpful to build into the algorithms an adaptive control mechanism such as a state-space search procedure. Such a procedure dynamically determines an optimal sequence of image processing operators to classify an image or to put its parts into correspondence with a model or set of models. One benefit of structuring the vision algorithm as a state-space search is that a multiplicity of paths toward goal nodes in the state space can be explored concurrently. In this paper, we identify several types of parallelism that may be exploited in vision algorithms based on state-space search. We present a new method, the 'V* algorithm', which, unlike earlier parallel search algorithms, generates the successors of a state in parallel. In machine vision, this part of the search process is very expensive, and thus V* permits substantial speedup. An experimental evaluation of V* is presented which is based on a simulation of a character recognition algorithm;the simulation runs on a Sequent Balance 21000 using 16 processors.

关键词： PARALLEL PROCESSING STATE SPACE SEARCH vision algorithm PARALLEL SEARCH

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Nonlinear control design using Takagi-Sugeno fuzzy applied to under-actuated visual servo system

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2020年第15期42卷 2969-2983页

作者： Jonnalagadda, Vimala Kumari Elumalai, Vinodh Kumar Singh, Harvir Prasad, Amit Vellore Inst Technol Sch Elect Engn Vellore 632014 Tamil Nadu India

This paper presents the Takagi-Sugeno (TS) fuzzy control design for nonlinear stabilization and tracking control of a ball on plate system. To deal with the plant nonlinearity and the fuzzy convergence issue, we formulate the parallel distributed compensator (PDC) TS fuzzy model to characterize the global behaviour of the nonlinear system and synthesize a feasible control framework using a velocity compensation scheme. The nonlinear dynamics of the ball on plate system is obtained using the Euler-Lagrangian energy based approach. To identify the moving objects in the video stream, a background subtraction algorithm using thresholding technique is formulated. Moreover, the stability analysis of the TS fuzzy control is reduced to linear matrix inequality (LMI) problem and solved using the Lyapunov direct method. The potential benefits of the proposed control structure for real time test cases are experimentally assessed using hardware in loop (HIL) testing on a ball on plate system. Experimental results substantiate that the TS fuzzy scheme can significantly improve not only the tracking performance but also the robustness of the closed loop system.

关键词： TS fuzzy Lyapunov stability ball on plate system vision algorithm

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Motion estimation of UAV based on video streaming

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JOURNAL OF AERONAUTICS ASTRONAUTICS AND AVIATION 2016年第3期48卷 141-148页

作者： Wang Hongfei Li Yongwei Hebei Univ Sci & Technol Sch Elect Engn Shijiazhuang 050000 Hebei Peoples R China

This paper describes a way of the motion estimation of four-rotor UAV based on video streaming, mainly researches the real-time vision algorithms, comprehensively completes video stream computing and understanding, and completes the reconstruction of UAV three-dimensional motion and structure. The study gives a solution of motion estimation of UAV that it is full embedded, light weight, low-cost autonomous positioning based on video streaming in arbitrary and unknown environment. In this paper, the calculation is based on the triple nested Kalman filter (3NKF) and 3NKF can synthesis three distinct areas (video stream computation, data fusion, restore the structure from motion) in a proper way.

关键词： video streaming vision algorithm quad-rotor UAV Kalman filter motion estimation

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Identification of Autonomous Landing Sign for Unmanned Aerial Vehicle Based on Faster Regions with Convolutional Neural Network

Identification of Autonomous Landing Sign for Unmanned Aeria...

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Chinese Automation Congress (CAC)

作者： Chen, Junjie Miao, Xiren Jiang, Hao Chen, Jing Liu, Xinyu Fuzhou Univ Coll Elect Engn & Automat Fuzhou Fujian Peoples R China

ISBN: (纸本)9781538635247

In order to realize autonomous landing of the unmanned aerial vehicle (UAV) in power patrolling, a visual method vision based on Faster Regions with Convolutional Neural Network (Faster R-CNN) for UAVs is studied. In this paper, we design the landing sign of the combination of concentric circles and pentagon,and propose the Faster R-CNN recognition algorithm which can be used to identify the target sign. Faster R-CNN successfully identifying the landing mark is the most important step for the UAV autonomous landing. Then, the estimation algorithm of position and direction based on vision is proposed. Position and direction for the UAV landing can be obtained based on least squares ellipse fitting and Shi-Tomasi corner detection method after the landing sign is effectively identified by Faster R-CNN. The experimental results show that it can achieve recognition speed of nearly 81 millisecond each frame and 97.8% accuracy by using Faster R-CNN for detection and identification. The proposed method has better identification accuracy compared with three target identification methods, the Support Vector Machine (SVM) classification, the Back Propagation (BP) neural network and You Only Look Once (YOLO) based on deep learning. The position and direction estimation error of the vision algorithm is within the allowable range, and it can meet the UAV real-time landing requirements.

关键词： autonomous landing vision algorithm deep learning object detection Faster R-CNN visual estimation

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