Computer Analysis of Images and Patterns


Book Description

Computer analysis of images and patterns is a scienti c eld of longstanding tradition, with roots in the early years of the computer era when electronic brains inspired scientists. Moreover, the design of vision machines is a part of humanity’s dream of the arti cial person. I remember the 2nd CAIP, held in Wismar in 1987. Lectures were read in German, English and Russian, and proceedings were also only partially written in English. The conference took place under a di erent political system and proved that ideas are independent of political walls. A few years later the Berlin Wall collapsed, and Professors Sommer and Klette proposed a new formula for the CAIP: let it be held in Central and Eastern Europe every second year. There was a sense of solidarity with scienti c communities in those countries that found themselves in a state of transition to a new economy. A well-implemented idea resulted in a chain of successful events in Dresden (1991), Budapest (1993), Prague (1995), Kiel (1997), and Ljubljana (1999). This year the conference was welcomed at Warsaw. There are three invited lectures and about 90 contributions written by more than 200 authors from 27 countries. Besides Poland (60 authors), the largest representation comes from France (23), followed by England (16), Czech Republic (11), Spain (10), G- many (9), and Belarus (9). Regrettably, in spite of free registration fees and free accommodation for authors from former Soviet Union countries, we received only one accepted paper from Russia.




Stochastic Image Processing


Book Description

Stochastic Image Processing provides the first thorough treatment of Markov and hidden Markov random fields and their application to image processing. Although promoted as a promising approach for over thirty years, it has only been in the past few years that the theory and algorithms have developed to the point of providing useful solutions to old and new problems in image processing. Markov random fields are a multidimensional extension of Markov chains, but the generalization is complicated by the lack of a natural ordering of pixels in multidimensional spaces. Hidden Markov fields are a natural generalization of the hidden Markov models that have proved essential to the development of modern speech recognition, but again the multidimensional nature of the signals makes them inherently more complicated to handle. This added complexity contributed to the long time required for the development of successful methods and applications. This book collects together a variety of successful approaches to a complete and useful characterization of multidimensional Markov and hidden Markov models along with applications to image analysis. The book provides a survey and comparative development of an exciting and rapidly evolving field of multidimensional Markov and hidden Markov random fields with extensive references to the literature.




Image Processing '92 (Icip '92) - Proceedings Of The 2nd Singapore International Conference


Book Description

This volume contains papers on Image Compression, Implementations, Feature Detection, 3-D Vision, Document Processing, Multi-Resolution Processing, Medical Imaging, Image Analysis Modelling, Neural Networks, Object Recognition, Remote Sensing, Dynamic Vision, Application, System & Architecture, Image Restoration/Enhancement and Image Segmentation.




Fourth IEEE Southwest Symposium on Image Analysis and Interpretation


Book Description

From down where the computer--or at least the computer images--are bigger than elsewhere, 59 papers cover segmentation; stereo image analysis; multiresolution, multispectral, and multidimensional analysis; biomedical and color image analysis; and features and invariants. Texts of the two keynotes are not included. A large poster session generated papers on such topics as a neural network approach to geographic image analysis, determining camera position through the Karhunen-Loeve transform, the efficient indexing of multi-color sets for content-based image retrieval, characterizing skin lesion texture in diffuse reflectance spectroscopic images, the knowledge-based extraction of roads from satellite images with one-meter resolution, detecting seat occupation inside vehicles, and segmentation by color space transformation prior to lifting and integer wavelet transformation for efficient lossless coding and transmission. Only authors are indexed. Annotation copyrighted by Book News, Inc., Portland, OR.




Markov Random Field Modeling in Image Analysis


Book Description

Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This third edition includes the most recent advances and has new and expanded sections on topics such as: Bayesian Network; Discriminative Random Fields; Strong Random Fields; Spatial-Temporal Models; Learning MRF for Classification. This book is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses in these areas.




Image Analysis and Recognition


Book Description

This book constitutes the thoroughly refereed proceedings of the 7th International Conference, ICIAR 2010, held in Póvoa de Varzin, Portugal in June 2010. The 88 revised full papers were selected from 164 submissions. The papers are organized in topical sections on Image Morphology, Enhancement and Restoration, Image Segmentation, Featue Extraction and Pattern Recognition, Computer Vision, Shape, Texture and Motion Analysis, Coding, Indexing, and Retrieval, Face Detection and Recognition, Biomedical Image Analysis, Biometrics and Applications.




Energy Minimization Methods in Computer Vision and Pattern Recognition


Book Description

This book constitutes the refereed proceedings of the International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR'97, held in Venice, Italy, in May 1997. The book presents 29 revised full papers selected from a total of 62 submissions. Also included are four full invited papers and a keynote paper by leading researchers. The volume is organized in sections on contours and deformable models, Markov random fields, deterministic methods, object recognition, evolutionary search, structural models, and applications. The volume is the first comprehensive documentation of the application of energy minimization techniques in the areas of compiler vision and pattern recognition.




Image Analysis and Processing


Book Description

This book presents the proceedings of the 8th International Conference on Image Analysis and Processing, ICIAP '95, held in Sanremo, Italy in September 1995 under the sponsorship of the International Association of Pattern Recognition IAPR. The volume presents 108 papers selected from more than 180 submissions together with six invited contributions. The papers are written by a total of 265 contributing authors and give a comprehensive state-of-the-art report on all current issues of image analysis and processing. Theoretical aspects are addressed as well as systems design and advanced applications, particularly in medical imaging.




Bayesian Inference for Inverse Problems


Book Description