This book constitutes the refereed proceedings of the 6th Mexican Conference on Pattern Recognition, MCPR 2014, held in Cancun, Mexico, in June 2014. The 39 revised full papers presented were carefully reviewed and selected from 68 submissions and are organized in topical sections on pattern recognition and artificial intelligence; computer vision; image processing and analysis; animal biometric recognition and applications of pattern recognition.

Cyberspace in increasingly important to people in their everyday lives for purchasing goods on the Internet, to energy supply increasingly managed remotely using Internet protocols. Unfortunately, this dependence makes us susceptible to attacks from nation states, terrorists, criminals and hactivists. Therefore, we need a better understanding of cyberspace, for which patterns, which are predictable regularities, may help to detect, understand and respond to incidents better. The inspiration for the workshop came from the existing work on formalising design patterns applied to cybersecurity, but we also need to understand the many other types of patterns that arise in cyberspace.

The book presents three most significant areas in Biometrics and Pattern Recognition. A step-by-step approach for design and implementation of Dual Tree Complex Wavelet Transform (DTCWT) plus Rotated Complex Wavelet Filters (RCWF) is discussed in detail. In addition to the above, the book provides detailed analysis of iris images and two methods of iris segmentation. It also discusses simplified study of some subspace-based methods and distance measures for iris recognition backed by empirical studies and statistical success verifications.

This book presents a thorough and detailed guide to image registration, outlining the principles and reviewing state-of-the-art tools and methods. The book begins by identifying the components of a general image registration system, and then describes the design of each component using various image analysis tools. The text reviews a vast array of tools and methods, not only describing the principles behind each tool and method, but also measuring and comparing their performances using synthetic and real data. Features: discusses similarity/dissimilarity measures, point detectors, feature extraction/selection and homogeneous/heterogeneous descriptors; examines robust estimators, point pattern matching algorithms, transformation functions, and image resampling and blending; covers principal axes methods, hierarchical methods, optimization-based methods, edge-based methods, model-based methods, and adaptive methods; includes a glossary, an extensive list of references, and an appendix on PCA.

This volume constitutes the proceedings of the 9th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2014, held in Salamanca, Spain, in June 2014. The 61 papers published in this volume were carefully reviewed and selected from 199 submissions. They are organized in topical sessions on HAIS applications; data mining and knowledge discovery; video and image analysis; bio-inspired models and evolutionary computation; learning algorithms; hybrid intelligent systems for data mining and applications and classification and cluster analysis.

This book constitutes the refereed proceedings of the 25th Annual Symposium on Combinatorial Pattern Matching, CPM 2014, held in Moscow, Russia, in June 2014. The 28 revised full papers presented together with 5 invited talks were carefully reviewed and selected from 54 submissions. The papers address issues of searching and matching strings and more complicated patterns such as trees; regular expressions; graphs; point sets; and arrays. The goal is to derive combinatorial properties of such structures and to exploit these properties in order to achieve superior performance for the corresponding computational problems. The meeting also deals with problems in computational biology; data compression and data mining; coding; information retrieval; natural language processing; and pattern recognition.

This book constitutes the refereed proceedings of the 5th International Conference on Information Processing in Computer-Assisted Interventions, IPCAI 2014, held in Fukuoka, Japan, on June 28, 2014. The 28 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on planning, simulation, patient specific models for computer assisted interventions, medical robotics and surgical navigation, interventional imaging and advanced intra-op visualization, cognition, modeling and context awareness, clinical applications, systems, software, and validation.

This volume constitutes the refereed proceedings of the 16th International Workshop on Combinatorial Image Analysis, IWCIA 2014, held in Brno, Czech Republic, in May 2014. The 20 revised full papers and 3 invited papers presented were carefully reviewed and selected from numerous submissions. The topics covered include discrete geometry and topology in imaging science, new results in image representation, segmentation, grouping, and reconstruction, medical image processing.

This indispensable text introduces the foundations of three-dimensional computer vision and describes recent contributions to the field. Fully revised and updated, this much-anticipated new edition reviews a range of triangulation-based methods, including linear and bundle adjustment based approaches to scene reconstruction and camera calibration, stereo vision, point cloud segmentation, and pose estimation of rigid, articulated, and flexible objects. Also covered are intensity-based techniques that evaluate the pixel grey values in the image to infer three-dimensional scene structure, and point spread function based approaches that exploit the effect of the optical system. The text shows how methods which integrate these concepts are able to increase reconstruction accuracy and robustness, describing applications in industrial quality inspection and metrology, human-robot interaction, and remote sensing.

The last decade has witnessed a rapid surge of interest in new sensing and monitoring devices for wellbeing and healthcare. One key development in this area is wireless, wearable and implantable "in vivo" monitoring and intervention. A myriad of platforms are now available from both academic institutions and commercial organisations. They permit the management of patients with both acute and chronic symptoms, including diabetes, cardiovascular diseases, treatment of epilepsy and other debilitating neurological disorders. Despite extensive developments in sensing technologies, there are significant research issues related to system integration, sensor miniaturisation, low-power sensor interface, wireless telemetry and signal processing.

In the 2nd edition of this popular and authoritative reference on Body Sensor Networks (BSN), major topics related to the latest technological developments and potential clinical applications are discussed, with contents covering.

Biosensor Design, Interfacing and Nanotechnology

Wireless Communication and Network Topologies

Communication Protocols and Standards

Energy Harvesting and Power Delivery

Ultra-low Power Bio-inspired Processing

Multi-sensor Fusion and Context Aware Sensing

Autonomic Sensing

Wearable, Ingestible Sensor Integration and Exemplar Applications

System Integration and Wireless Sensor Microsystems

The book also provides a comprehensive review of the current wireless sensor development platforms and a step-by-step guide to developing your own BSN applications through the use of BSN development kit.

Although the capabilities of computer image analysis do not yet match those of the human visual system, recent developments have made great progress towards tackling the challenges posed by the perceptual analysis of images.

This unique text/reference highlights a selection of important, practical applications of advanced image analysis methods for medical images. The book covers the complete methodology for processing, analysing and interpreting diagnostic results of sample computed tomography (CT) images. The text also presents significant problems related to new approaches and paradigms in image understanding and semantic image analysis. To further engage the reader, example source code is provided for the implemented algorithms in the described solutions.

Topics and features: describes the most important methods and algorithms used for image analysis, including holistic and syntactic methods; examines the fundamentals of cognitive computer image analysis for computer-aided diagnosis and semantic image description, introducing the cognitive resonance model; presents original approaches for the semantic analysis of CT perfusion and CT angiography images of the brain and carotid artery; discusses techniques for creating 3D visualisations of large datasets, and efficient and reliable algorithms for 3D rendering; reviews natural user interfaces in medical imaging systems, covering innovative Gesture Description Language technology; concludes with a summary of significant developments in advanced image recognition techniques and their practical applications, along with possible directions for future research.

This cutting-edge work is an invaluable practical resource for researchers and professionals interested in medical informatics, computer-aided diagnosis, computer graphics, and intelligent information systems.

This book constitutes the proceedings of the International Conference on Adaptive and Intelligent Systems, ICAIS 2014, held in Bournemouth, UK, in September 2014. The 19 full papers included in these proceedings together with the abstracts of 4 invited talks, were carefully reviewed and selected from 32 submissions. The contributions are organized under the following topical sections: advances in feature selection; clustering and classification; adaptive optimization; advances in time series analysis.

Dialect Accent Features for Establishing Speaker Identity: A Case Study discusses the subject of forensic voice identification and speaker profiling. Specifically focusing on speaker profiling and using dialects of the Hindi language, widely used in India, the authors have contributed to the body of research on speaker identification by using accent feature as the discriminating factor. This case study contributes to the understanding of the speaker identification process in a situation where unknown speech samples are in different language/dialect than the recording of a suspect. The authors' data establishes that vowel quality, quantity, intonation and tone of a speaker as compared to Khariboli (standard Hindi) could be the potential features for identification of dialect accent.

"Reliable Knowledge Discovery" focuses on theory, methods, and techniques for RKDD, a new sub-field of KDD. It studies the theory and methods to assure the reliability and trustworthiness of discovered knowledge and to maintain the stability and consistency of knowledge discovery processes. RKDD has a broad spectrum of applications, especially in critical domains like medicine, finance, and military.

"Reliable Knowledge Discovery" also presents methods and techniques for designing robust knowledge-discovery processes. Approaches to assessing the reliability of the discovered knowledge are introduced. Particular attention is paid to methods for reliable feature selection, reliable graph discovery, reliable classification, and stream mining. Estimating the data trustworthiness is covered in this volume as well. Case studies are provided in many chapters.

"Reliable Knowledge Discovery" is designed for researchers and advanced-level students focused on computer science and electrical engineering as a secondary text or reference. Professionals working in this related field and KDD application developers will also find this book useful.

Financial identity theft is well understood with clear underlying motives. Medical identity theft is new and presents a growing problem. The solutions to both problems however, are less clear.

The Economics of Financial and Medical Identity Theft discusses how the digital networked environment is critically different from the world of paper, eyeballs and pens. Many of the effective identity protections are embedded behind the eyeballs, where the presumably passive observer is actually a fairly keen student of human behavior. The emergence of medical identity theft and the implications of medical data privacy are described in the second section of this book.

The Economics of Financial and Medical Identity Theft also presents an overview of the current technology for identity management. The book closes with a series of vignettes in the last chapter, looking at the risks we may see in the future and how these risks can be mitigated or avoided.

The classification of patterns is an important area of research which is central to all pattern recognition fields, including speech, image, robotics, and data analysis. Neural networks have been used successfully in a number of these fields, but so far their application has been based on a 'black box approach' with no real understanding of how they work. In this book, Sarunas Raudys - an internationally respected researcher in the area - provides an excellent mathematical and applied introduction to how neural network classifiers work and how they should be used.. .

This book constitutes the thoroughly refereed post-workshop proceedings of the Third International Workshop on Medical Computer Vision, MCV 2013, held in Nagoya, Japan, in September 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013. The 7 revised full papers and 12 poster papers presented were selected from 25 submissions. They have been organized in topical sections on registration and visualization, segmentation, detection and localization, and features and retrieval. In addition, the volume contains two invited papers describing segmentation task and data set of the VISCERAL benchmark challenge.

This research book provides a comprehensive overview of the state-of-the-art subspace learning methods for pattern recognition in intelligent environment. With the fast development of internet and computer technologies, the amount of available data is rapidly increasing in our daily life. How to extract core information or useful features is an important issue. Subspace methods are widely used for dimension reduction and feature extraction in pattern recognition. They transform a high-dimensional data to a lower-dimensional space (subspace), where most information is retained. The book covers a broad spectrum of subspace methods including linear, nonlinear and multilinear subspace learning methods and applications. The applications include face alignment, face recognition, medical image analysis, remote sensing image classification, traffic sign recognition, image clustering, super resolution, edge detection, multi-view facial image synthesis.

This book constitutes the refereed proceedings of the First International Conference on Biomedical Informatics and Technology, ACBIT 2013, held in Aizu-Wakamatsu, Japan, in September 2013. The ??? revised full papers presented together with 14 keynotes and invited talks were carefully reviewed and selected from 48 submissions. The papers address important problems in medicine, biology and health using image analysis, computer vision, pattern analysis and classification, information visualization, signal processing, control theory, information theory, statistical analysis, information fusion, numerical analysis, fractals and chaos, optimization, simulation and modeling, parallel computing, computational intelligence methods, machine learning, data mining, decision support systems, database integration and management, cognitive modeling, and applied linguistics.

This book constitutes revised selected papers from the International Workshop on Clinical Image-Based Procedures, CLIP 2013, held in conjunction with MICCAI 2012 in Nagoya, Japan, in September 2013. The 19 papers presented in this volume were carefully reviewed and selected from 26 submissions. The workshop was a productive and exciting forum for the discussion and dissemination of clinically tested, state-of-the-art methods for image-based planning, monitoring and evaluation of medical procedures.

This book constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Camera-Based Document Analysis and Recognition, CBDAR 2013, held in Washington, DC, USA, in August 2013. The 14 revised full papers presented were carefully selected during two rounds of reviewing and improvement from numerous original submissions. Intended to give a snapshot of the state-of-the-art research in the field of camera based document analysis and recognition, the papers are organized in topical sections on text detection and recognition in scene images and camera-based systems.

This edited collection will provide an overview of the field of physiological computing, i.e. the use of physiological signals as input for computer control. It will cover a breadth of current research, from brain-computer interfaces to telemedicine.

Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical. David Hilbert The goal of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety of applications. We try to achieve this by presenting the basic ideas of SVMs together with the latest developments and current research questions in a uni?ed style. In a nutshell, we identify at least three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness against several types of model violations and outliers, and last but not least their computational e?ciency compared with several other methods. Although there are several roots and precursors of SVMs, these methods gained particular momentum during the last 15 years since Vapnik (1995, 1998) published his well-known textbooks on statistical learning theory with aspecialemphasisonsupportvectormachines. Sincethen,the?eldofmachine learninghaswitnessedintenseactivityinthestudyofSVMs,whichhasspread moreandmoretootherdisciplinessuchasstatisticsandmathematics. Thusit seems fair to say that several communities are currently working on support vector machines and on related kernel-based methods. Although there are many interactions between these communities, we think that there is still roomforadditionalfruitfulinteractionandwouldbegladifthistextbookwere found helpful in stimulating further research. Many of the results presented in this book have previously been scattered in the journal literature or are still under review. As a consequence, these results have been accessible only to a relativelysmallnumberofspecialists,sometimesprobablyonlytopeoplefrom one community but not the others.

This book constitutes the refereed proceedings of the 9th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2013, held in Vienna, Austria, in May 2013. The 24 papers presented in this volume were carefully reviewed and selected from 27 submissions. They are organized in topical sections named: finding subregions in graphs; graph matching; classification; graph kernels; properties of graphs; topology; graph representations, segmentation and shape; and search in graphs.

The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XVII is a continuation of a number of research streams which have grown out of the seminal work by Zdzislaw Pawlak during the first decade of the 21st century. The research streams represented in the papers cover both theory and applications of rough, fuzzy and near sets as well as their combinations.