The Autonomous Image:Cinematic Narration and Humanism Armando J. Prats
Autonomous Image: A. J. Prats, Armando J. Prats
Image Dependent Relative Formation Navigation for Autonomous Aerial Refueling: James Michael Howard
Processing Imagery for Low-Cost Autonomous Remote Sensing Platforms:A Geospatial Real-Time Aerial Image Display for a Low-Cost Autonomous Multispectral Remote Sensing Platform (AggieAir) Austin Jensen
Processing Imagery for Low-Cost Autonomous Remote Sensing Platforms ab 49 EURO A Geospatial Real-Time Aerial Image Display for a Low-Cost Autonomous Multispectral Remote Sensing Platform (AggieAir)
This edited volume contains technical contributions in the field of computer vision and image processing presented at the First International Conference on Computer Vision and Image Processing (CVIP 2016). The contributions are thematically divided based on their relation to operations at the lower, middle and higher levels of vision systems, and their applications. The technical contributions in the areas of sensors, acquisition, visualization and enhancement are classified as related to low-level operations. They discuss various modern topics - reconfigurable image system architecture, Scheimpflug camera calibration, real-time autofocusing, climate visualization, tone mapping, super-resolution and image resizing. The technical contributions in the areas of segmentation and retrieval are classified as related to mid-level operations. They discuss some state-of-the-art techniques - non-rigid image registration, iterative image partitioning, egocentric object detection and video shot boundary detection. The technical contributions in the areas of classification and retrieval are categorized as related to high-level operations. They discuss some state-of-the-art approaches - extreme learning machines, and target, gesture and action recognition. A non-regularized state preserving extreme learning machine is presented for natural scene classification. An algorithm for human action recognition through dynamic frame warping based on depth cues is given. Target recognition in night vision through convolutional neural network is also presented. Use of convolutional neural network in detecting static hand gesture is also discussed. Finally, the technical contributions in the areas of surveillance, coding and data security, and biometrics and document processing are considered as applications of computer vision and image processing. They discuss some contemporary applications. A few of them are a system for tackling blind curves, a quick reaction target acquisition and tracking system, an algorithm to detect for copy-move forgery based on circle block, a novel visual secret sharing scheme using affine cipher and image interleaving, a finger knuckle print recognition system based on wavelet and Gabor filtering, and a palmprint recognition based on minutiae quadruplets. Dr. R. Balasubramanian is currently an associate professor in the department of Computer Science and Engineering at IIT Roorkee, India. He completed his Ph.D. (Mathematics and Computer Science) from Indian Institute of Technology Madras, Chennai in 2001. His areas of interest include Computer Vision - Optical Flow Problems, Fractional Transform Theory, Wavelet Analysis, Image and Video Processing, Multimedia Security: Digital Image Watermarking and Encryption, Biometrics, Content Based Image and Video Retrieval, Hyperspectral and Microwave Imaging and Visualization, Volume Graphics. He has published over 80 papers in refereed journal and contributed 7 chapters in books. Dr. Sanjeev Kumar is an assistant professor of Mathematics at IIT Roorkee, India. His areas of interest are Computer Vision & Mathematical Imaging, Inverse Problems, and Machine Learning, He completed his Ph.D. in mathematics from IIT Roorkee in 2008. He is a member of IEEE Computer Society and International Association of Pattern Recognition and life member of ACEEE and IACSIT. He has got over 40 papers published in journals as well as conference proceedings. Dr. Partha Pratim Roy is an assistant professor of Computer Science and Engineering at IIT Roorkee, India. Before joining IIT Roorkee, he has worked with Samsung Research Institute Noida as chief engineer. He did his Ph.D. in Computer Science and Engineering (2010) from Autonomous University of Barcelona, Spain. He has got seve ral papers published in journals and international conference proceedings. His interest areas include Pattern Recognition, Multilingual Text Recognition, Biometrics, Identification and Verification of Signature, Fingerprint, etc., Computer Vision, Image Segmentation, Machine Learning, and Hidden Markov Model. Dr. Debashis Sen is Assistant Professor, Electronics & Electrical Communication Engineering at IIT Kharagpur, India. He did his Ph.D in Engineering (Image Processing) from Jadavpur University, Kolkata in 2011. He has got 12 papers published in journals, 13 in conference proceedings and 1 book chapter. His research areas are Vision Image and Video Processing, Uncertainty Handling, Bio-inspired Computation, Eye
This book provides the most recent findings and knowledge in advanced diagnostics technology, covering a wide spectrum including brain activity analysis, breast and lung cancer detection, echocardiography, computer aided skeletal assessment to mitochondrial biology imaging at the cellular level. The authors explored magneto acoustic approaches and tissue elasticity imaging for the purpose of breast cancer detection. Perspectives in fetal echocardiography from an image processing angle are included. Diagnostic imaging in the field of mitochondrial diseases as well as the use of Computer-Aided System (CAD) are also discussed in the book. This book will be useful for students, lecturers or professional researchers in the field of biomedical sciences and image processing. Dr. Lai Khin Wee, MIET, received his PhD in Biomedical Engineering under DAAD PhD sandwich program between Technische Universität Ilmenau, Germany and Universiti Teknologi Malaysia, Johor Bahru. He is currently working as senior lecturer at University Malaya. His research interests include medical imaging and medical computing. Dr. Hum Yan Chai received his PhD in the field of biomedical imaging from the Universiti Teknologi Malaysia (UTM). He is currently working as senior researcher MIMOS Berhad. His research interests include medical image processing, fuzzy logic, and medical computing. Dr. Salim Maheza Irna Mohamad received her Doctoral degree in Medical Imaging from Universiti Teknologi Malaysia in 2012. She is currently a Senior Lecturer at Universiti Teknologi Malaysia. Her research interest includes Medical Imaging and instrumentation, especially ultrasound and hybrid imaging for cancer research application. Dr. Sang-Bing Ong, PhD CBiol EurProBiol, first demonstrated the relevance of mitochondrial morphology in the heart and its relation to cardioprotection during his doctoral studies at the Hatter Cardiovascular Institute at University College London (UCL). He then moved to the University of California, San Diego (UCSD) for further research in mitochondrial biology. He is currently a Senior Lecturer at Universiti Teknologi Malaysia. Dr. Nugraha P. Utama received his PhD from the Tokyo Institute of Technology specializing in Human Machine Interface and Neuroscience. After receiving his PhD, he became a post-doctoral fellow in the precision and intelligent systems laboratory, Tokyo Institute of Technology. He is currently served as senior lecturer at Universiti Teknologi Malaysia. His research interests are in neuroscience and assistive technology. Dr. Myint Yin Mon received her Ph.D from Yangon Technological University, Myanmar. Since 2011, she is working as a senior lecturer in the Department of Bioscience and Medical Engineering at UTM. Her current research interests are image guided autonomous robot systems and medical imaging systems. Dr. Norliza Mohd Noor received her PhD in Elect. Eng. from Universiti Teknologi Malaysia. She is currently an Associate Professor at UTM Razak School of Engineering and Advanced Technology, UTM International Campus, Kuala Lumpur. Her research interest is in image processing and analysis for medical and industrial application. Dr. Eko Supriyanto is the Director of IJN-UTM Cardiovascular Engineering Centre as well as Head of Advanced Diagnostics Research Group, University Technology Malaysia. He obtained Doctor of Engineering from University of Federal Armed Forces Hamburg Germany. His interest research areas are ultrasound, electronics and computer application in medicine and industry.
This book presents a careful selection of the contributions presented at the Mathematical Methods in Engineering (MME10) International Symposium, held at the Polytechnic Institute of Coimbra- Engineering Institute of Coimbra (IPC/ISEC), Portugal, October 21-24, 2010. The volume discusses recent developments about theoretical and applied mathematics toward the solution of engineering problems, thus covering a wide range of topics, such as: Automatic Control, Autonomous Systems, Computer Science, Dynamical Systems and Control, Electronics, Finance and Economics, Fluid Mechanics and Heat Transfer, Fractional Mathematics, Fractional Transforms and Their Applications, Fuzzy Sets and Systems, Image and Signal Analysis, Image Processing, Mechanics, Mechatronics, Motor Control and Human Movement Analysis, Nonlinear Dynamics, Partial Differential Equations, Robotics, Acoustics, Vibration and Control, and Wavelets.
This book focuses on light invariant bare hand gesture recognition while there is no restriction on the types of gestures. Observations and results have confirmed that this research work can be used to remotely control a robotic hand using hand gestures. The system developed here is also able to recognize hand gestures in different lighting conditions. The pre-processing is performed by developing an image-cropping algorithm that ensures only the area of interest is included in the segmented image. The segmented image is compared with a predefined gesture set which must be installed in the recognition system. These images are stored and feature vectors are extracted from them. These feature vectors are subsequently presented using an orientation histogram, which provides a view of the edges in the form of frequency. Thereby, if the same gesture is shown twice in different lighting intensities, both repetitions will map to the same gesture in the stored data. The mapping of the segmented images orientation histogram is firstly done using the Euclidian distance method. Secondly, the supervised neural network is trained for the same, producing better recognition results. An approach to controlling electro-mechanical robotic hands using dynamic hand gestures is also presented using a robot simulator. Such robotic hands have applications in commercial, military or emergency operations where human life cannot be risked. For such applications, an artificial robotic hand is required to perform real-time operations. This robotic hand should be able to move its fingers in the same manner as a human hand. For this purpose, hand geometry parameters are obtained using a webcam and also using KINECT. The parameter detection is direction invariant in both methods. Once the hand parameters are obtained, the fingers angle information is obtained by performing a geometrical analysis. An artificial neural network is also implemented to calculate the angles. These two methods can be used with only one hand, either right or left. A separate method that is applicable to both hands simultaneously is also developed and fingers angles are calculated. The contents of this book will be useful for researchers and professional engineers working on robotic arm/hand systems. Dr. Ankit Chaudhary received his Master of Engineering degree in Computer Science from the Birla Institute of Technology and Science, Pilani and his Ph.D. from the Central Electronics Engineering Research Institute, Council of Scientific and Industrial Research (CSIR). His research interests include vision-based applications, intelligent systems, and Robotics. Having authored sixty research publications and edited one book, Dr. Chaudhary is an Associate Editor for Computers and Electrical Engineering and serves on the Editorial Boards of several international journals. He is also a reviewer for numerous journals, including IEEE Transactions on Image Processing, IET Image Processing, Machine Vision and Applications, and Robotics and Autonomous Systems. In the past, Dr. Chaudhary was associated with the University of Iowas Department of Electrical and Computer Engineering and the Department of Computer Science BITS Pilani, also working as a Visiting Faculty/researcher at many research laboratories.
This book proposes a new approach to handle the problem of limited training data. Common approaches to cope with this problem are to model the shape variability independently across predefined segments or to allow artificial shape variations that cannot be explained through the training data, both of which have their drawbacks. The approach presented uses a local shape prior in each element of the underlying data domain and couples all local shape priors via smoothness constraints. The book provides a sound mathematical foundation in order to embed this new shape prior formulation into the well-known variational image segmentation framework. The new segmentation approach so obtained allows accurate reconstruction of even complex object classes with only a few training shapes at hand. Carsten Last received his diploma degree in computer and communications systems engineering (with distinction) from TU Braunschweig, Germany, in 2009. During his studies he worked as a student assistant in the area of speech enhancement at the Institute for Communications Technology at TU Braunschweig. From 2009 to 2015 he was a research assistant and PhD student at the Institute for Robotics and Process Control at TU Braunschweig, from which he received his doctorate degree in computer science in 2016 (summa cum laude). His research focused mainly on the areas of medical image processing and computer vision. Since 2015, he is working as a research engineer at Volkswagen AG in the area of autonomous driving.