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2016 IEEE international conference on Signal and image processing

作者： Yi Wang Zhonghua Luo Zhihai Xu Huajun Feng Qi Li Yueting Chen State Key Lab of Modern Optical Instrumentation Zhejiang University The No.59 Research Institute of China Ordnance Industry

As an important research area in image analysis and computer vision, fusion of infrared and visible images aims at delivering an effective combination of image information from different *** the final fused image is the demonstration of fusion process, it should reveal both source images' vital information *** achieve this purpose, an image fusion method based on multiscale hybrid unidirectional total variation(MHUTV) and visual weight map(VWM) is proposed in this *** MHUTV combines the feature of extracting the details from images and the capacity of suppressing stripe noise, which leads to a more ideal visual *** MHUTV is a multiscale, unidirectional and self-adaption image decomposition method, which is used to fuse infrared and visible images in this *** visual weight map aims to reveal attention drawing distribution of human *** provides a subband fusion criterion, which can guarantee the highlighting of interesting area from infrared and visible ***, multiscale hybrid unidirectional total variation is discussed and used to decompose the source images into approximation subbands and detail ***, the approximation and details subbands are respectively fused by a fusion rule based on visual weight ***, the fused subbands are combined into one image by implementing inverse *** results of comparison experiments on different sets of images demonstrate the effectiveness of the proposed method.

关键词： image fusion image denoise infrared image multiscale decompose visible image

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Foreword

Proceedings of the 2016 International Conference on Image Pr...

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Proceedings of the 2016 international conference on image processing, computer vision, and Pattern Recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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Detection of abnormal moving vehicles for intelligent driver assistance system

Detection of abnormal moving vehicles for intelligent driver...

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international conference on Electronics, Information and Communications (ICEIC)

作者： Cuong Nguyen Khac Ju H. Park Ho-Youl Jung Yeungnam University Gyeongsan Gyeongsangbuk-do KR Yeungnam University South Korea

ISBN: (纸本)9781467380171

Driving in nighttime environment is a difficult work due to low visibility, drowsy and impaired drivers. It is crucial to make a good algorithm to detect automatically abnormal moving vehicles surrounding the host vehicle to indicate early collision warning. This paper proposes an efficient approach to detect on-road abnormal moving vehicles in nighttime. Oncoming, change speed, change lane, roadside parking, and overtaking vehicles are detected. The proposal method is useful for vehicle behavior analysis system of IDAS (Intelligent Driver Assistance System). Firstly, all motion vectors of moving objects are estimated from frames. Most of safety moving vehicles are eliminated by using a new proposal threshold range and ROI setting. The remaining motion vectors are grouped by using K-means clustering algorithm to obtain segment abnormal vehicle candidates. The segmented candidates are classified using learning algorithm Support Vector Machines (SVMs) and various features to eliminate non-vehicle candidates. The experimental results show that the proposal method is high ability to detect the abnormal moving vehicles in front of the host vehicle in nighttime driving. It is useful to be the first processing step for behavior analysis systems in Intelligent Driver Assistance Systems.

关键词： Vehicles Feature extraction Proposals Optical imaging image motion analysis computer vision Clustering algorithms

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Building Inclusiveness in a PBL Based Online Robotics Competition: Challenges and Outcomes

Building Inclusiveness in a PBL Based Online Robotics Compet...

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Learning and Teaching in Computing and Engineering (LaTiCE)

作者： Saraswathi Krithivasan Saurav Shandilya Sanam Shakya Kavi Arya Krishna Lala Department of Computer Science & Engineering Indian Institute of Technology Bombay Powai Mumbai India

e-Yantra conducts an annual online competition, e-Yantra Robotics Competition (eYRC) which incorporates a Project-Based Learning (PBL) methodology to train students to implement a robotics project in a step-by-step manner over a five month period. The competition is designed to provide all the resources - robot, accessories, and a project - to each participating team to make the competition accessible to students from the remotest parts of India. Every year the goal is to increase the number of participating teams selected through an online selection test. Even though multiple teams from a college qualify, we restrict the number of teams from a college to the number of unique "Themes" -- projects abstracted into rulebooks -- assigned in the competition. In eYRC-2013, 72 teams (out of 232 teams) who had qualified through the selection test could not be included in the competition, as we had only 5 unique Themes. In 2014, we started a parallel competition, eYRC+ Pilot to include all the qualifying teams. In this paper we describe the methodology used in this competition where we experimented with a Theme involving an advanced topic -- image processing - such that we could assign the same theme to more number of teams. Our analysis of performance of teams show that contrary to our hypothesis, the learning outcomes of teams in the various tasks assigned in the competition are comparable to that of teams participated in the eYRC themes. Analyzing the effectiveness of the competition in imparting PBL, based on feedback received from the teams, we find that eYRC+ is as effective as eYRC. We present our analysis and how we have applied it in the current edition of the competition eYRC-2015.

关键词： image processing Mobile robots Cameras Robot vision systems

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A Laser-vision based Obstacle Detection and Distance Estimation for Smart Wheelchair Navigation

A Laser-Vision based Obstacle Detection and Distance Estimat...

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2016 IEEE international conference on Signal and image processing

作者： Fitri Utaminingrum Tri Astoto Kurniawan M Ali Fauzi Rizal Maulana Dahnial Syauqy Randy Cahya Wihandika Yuita Arum Sari Putra Pandu Adikara Faculty of Computer Science Brawijaya University

The aim of the research is to present an approach of obstacle distance estimation and navigation for smart *** smart wheelchair is an electric wheelchair equipped with camera and line laser to navigate and avoid an *** camera was used to capture images from the environment to sense the pathway *** line laser was used in combination with camera to recognize an obstacle in the pathway based on the shape of line laser image in certain angle.A blob method detection was applied on the line laser image to recognize the pattern of the detected *** line laser projector and camera were mounted in fixed-certain position to make sure a fixed relation between blobs-gaps and obstacle-to-wheelchair distance.A simple linear regression from 16 obtained data was used to represent this relation as the estimated obstacle *** a result, the average error between the estimation and actual distance was 1.25 cm from 7 data testing *** experiments result indicates that the proposed method is able to estimate well the distance between wheelchair and ***, the smart wheelchair needs to decide further action whether it should turn left, right or just walk straight when facing certain obstacle to avoid it.

关键词： obstacle detection distance estimation line laser image blob method smart wheelchair

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Face recognition and detection using Random forest and combination of LBP and HOG features

Face recognition and detection using Random forest and combi...

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international conference on Smart Computing and Electronic Enterprise (ICSCEE)

作者： Huda Mady Shadi M. S. Hilles Dept. Computer Science Almadinah International University Kuala lumpur Malaysia

ISBN: (纸本)9781538648391

The effective facial recognition method should perform well in unregulated environments based on video broadcast to satisfy the demands of applications in real-world However, this still remains a big challenge for most current face recognition algorithms that will affect the accuracy of the system. This study was conducted to develop face recognition method based on video broadcast under illumination variation, facial expressions, different pose, orientation, occlusion, nationality variation and motion. Viola-Jones algorithm was applied to improve face detection which is these method have proven to detect the faces in an uncontrolled environment in the real world simply and high accuracy. A combination of Histograms of Oriented Gradients (HOG) and Local Binary Pattern (LBP) descriptors was conducted for faces features extraction purpose. These descriptors have proven to be lower computational time. The latest and accurate technique was applied for face classification based on Random Forest classifier (RF). To evaluate the efficiency of the Random Forest classifier, compared it with Support Vector Machine classifiers (SVM) is done with different existing feature extraction methods. Four experiments were implemented on Mediu staff database and excellent results have reported the efficiency of proposed algorithm average recognition accuracy 97.6% The computer vision and image processing MAT LAB 2016b Toolboxes was used for coding the desired system, dataset based on videos.

关键词： Face Face recognition Feature extraction Histograms Forestry Databases Lighting

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Rectification for fronto-parallel camera movement in 3D reconstruction of printed circuit boards

Rectification for fronto-parallel camera movement in 3D reco...

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IEEE Instrumentation and Measurement Technology conference

作者： Matthias Breier Patrick Küsters Anna König Wei Li Marcel Bosling Thomas Pretz Dorit Merhof Institute of Imaging and Computer Vision RWTH Aachen University Aachen Germany Department of Processing and Recycling RWTH Aachen University Aachen Germany

Recycling of printed circuit boards (PCBs) is one of the open challenges in research. For recycling, the identification of the components on PCBs is of great importance. For PCB component classification the height profile of a PCB is one of the important features. One approach to obtain this profile is photogrammetry employing different views of the PCB's surface. Thereby, rectification of the images is essential for highly accurate, dense 3D reconstruction employing block matchers. However, commonly utilized rectification approaches rely on the fundamental matrix which deteriorates in scenes with low depth structure. Thus, a new rectification approach is needed for the case of PCBs. We propose a homography-based approach employing salient image features which are tracked in the images of a camera moved fronto-parallel above the PCB. It can be shown that the accuracy of the 3D reconstruction after applying the proposed rectification allows reconstructing structures at 0.1mm accuracy. This is sufficient for detecting small surface mounted devices with a minimal height of 0.2 mm.

关键词： Cameras Transmission line matrix methods Feature extraction Three-dimensional displays Recycling Tracking Electronic waste

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A survey on applications of high dynamic range technologies in consumer electronic devices

A survey on applications of high dynamic range technologies ...

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international conference on Control, Automation and Systems ( ICCAS)

作者： YoungSu Moon Visual Display Division Samsung Electronics Co. Suwon-si Gyeonggi-do Korea

ISBN: (纸本)9781467390583

High dynamic range (HDR) technology is one of various research topics in computer vision technologies, which has been actively being applied to cutting-edge consumer electronics products such as premium UHDTV, premium smart phones and etc. In case of consumer camera devices or mobile camera phones, HDR scene capture mode is commonly provided by combining differently-exposed images with standard dynamic range (SDR). In consumer premium TVs, there exist two kinds of HDR processing technologies: one is a tone mapping (TM) to render HDR content on SDR display, and the other one is an inverse tone mapping (iTM) to render a SDR content on HDR display. Especially, in the case of HDR ton mapping, some metadata for adjusting radiometric difference between a reference mastering display and various consumer TV displays were standardized as well as HDR signal encoding method. Currently there exist various organizations related to HDR standards: UHD-Alliance, SMPTE, CTA, ITU-R, MPEG, DVB and etc. Those HDR standard ecosystem members include movie studio, broadcasting, OTTs, TV/STB manufacturers, and etc. They have made efforts to create a next big opportunity of brand-new HDR technology on the basis of 4K UHD media. We will here review HDR technologies, standards, delivery system, and its CE industry trends.

关键词： TV image color analysis Dynamic range Cameras Metadata SMPTE

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A Multi-objective Assignment Algorithm for UAVs in Multiple Task with Different Workloads

A Multi-objective Assignment Algorithm for UAVs in Multiple ...

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2023 Asia-Pacific conference on image processing, Electronics and computers, IPEC 2023

作者： Ding, Rui Zhu, Yuhan Feng, Xianbin Chai, Baojie Ji, Ran College of Computer Science and Information Technology Mudanjiang Normal University Heilongjiang Mudanjiang157000 China

ISBN: (纸本)9781665457033

UAVs have been widely used in military and civilian fields. The research on UAV task assignment mainly involves trajectory planning, task assignment, and specific applications for various scenarios. Moreover, most of the previous studies are for single UAV. Studies for swarm of UAVs are relatively few. In this paper, we focus on the multi-objective assignment algorithm of UAVs for multiple tasks which have homogeneous application scenarios with different locations, same priorities and different workloads. First, a coding method that can simultaneously reflect path planning and task allocation is designed, Based on this, a multiple task assignment algorithm for UAVs swarm is designed, In order to balance the tasks completion time, the workload of each task and the total transfer distance, a multi-objective assignment model is further constructed, and the complete multi-objective UAVs task assignment algorithm is proposed. The task assignment scheme obtained by the algorithm can make the UAVs complete all tasks in a balanced time and resource consumption. The experimental results show that our proposed method can determine the UAVs task assignment plan effectively and efficiently. © 2023 IEEE.

关键词： Multiobjective optimization

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2018年 703卷 v-vi页

作者： Chaudhuri, Bidyut B. Kankanhalli, Mohan S. Raman, Balasubramanian Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India School of Computing National University of Singapore Singapore Singapore Department of Computer Science and Engineering Indian Institute of Technology Roorkee RoorkeeUttarakhand India

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