Advances in Pattern Recognition
Springer Berlin (Verlag)
978-3-540-64858-1 (ISBN)
The book presents 107 revised full papers selected from 134 submissions. Also included are six invited presentations. The papers are organized in topical sections on structural matching and grammatical inference, recognition of 2D and 3D objects, document image analysis and recognition, handwritten character recognition, shape representation and image segmentation, learning methodologies, feature selection and extraction, statistical classification techniques, statistical pattern recognition, and rejection in pattern recognition.
Error-tolerant graph matching: A formal framework and algorithms.- Semantic content based image retrieval using object-process diagrams.- Pattern recognition methods in image and video databases: Past, present and future.- Efficient matching with invariant local descriptors.- Torah codes: New experimental protocols.- Integrating numerical and syntactic learning models for pattern recognition.- Synthesis of function-described graphs.- Marked subgraph isomorphism of ordered graphs.- Distance evaluation in pattern matching based on frontier topological graph.- Syntactic interpolation of fractal sequences.- Minimizing the topological structure of line images.- Genetic algorithms for structural editing.- The noisy subsequence tree recognition problem.- The path-connectedness in Z 2 and Z 3 and classical topologies.- Object recognition from large structural libraries.- Acquisition of 2-D shape models from scenes with overlapping objects using string matching.- A taxonomy of occlusion in viewsignature II representations: A regular language for the representation of 3-D rigid solid objects.- Skeletonizing volume objects part II: From surface to curve skeleton.- A survey of non-thinning based vectorization methods.- A benchmark for Raster to vector conversion systems.- Network-based recognition of architectural symbols.- Recovering image structure by model-based interaction map.- An improved scheme to fingerprint classification.- Character recognition with k-head finite array automata.- Using semantics in matching cursive Chinese handwritten annotations.- Concavity detection using a binary mask-based approach.- Structural indexing of line pictures with feature generation models.- Nonlinear covariance for multi-band image data.- A neural network for image smooothing and segmentation.- Prototyping structural descriptions: An inductive learning approach.- Neural network based learning of local compatibilities for segment grouping.- Constrained attribute grammars for recognition of multi-dimensional objects.- Object recognition using sequential images and application to active vision.- Recognizing partially visible 2-D non-rigid wire-shapes.- XFF: A simple method to extract fractal features for 2D object recognition.- Tracking of rotating objects.- Efficient implementation of regulated morphological operations based on directional interval coding.- Clique-to-clique distance computation using a specific architecture.- Algebraic view of grammatical inference.- Remarks on the notation of coordinate grammars.- A structural classifier to automatically identify form classes.- Towards efficient structural analysis of mathematical expressions.- The topological consistence of path connectedness in regular and irregular structures.- Content-based image indexing and retrieval: A syntactical approach.- Knowledge-based recognition of crosshatched areas in engineering drawings.- Information extraction from document images using white space and graphics analysis.- Multi-interval discretization methods for decision tree learning.- Handwritten digit recognition through inferring graph grammars. A first appproach.- Optical character recognition: Neural network analysis of hand-printed characters.- Structural boundary feature extraction for printed character recognition.- Locating segmentation regions of connected handwritten digits.- Recognition on handwritten digits based on their topological and morphological properties.- Perceptual features for off-line handwritten word recognition: A framework for heuristic prediction, representation and matching.- On structural modelling for omnifont and handwritten character recognition.- Image segmentation by label anisotropic diffusion.- Classifier-independent feature selection for two-stage feature selection.- Feature selection for a nonlinear classifier.- Regularization by adding redundant features.- Feature selection expert - User oriented approach.- Structures of the covariance matrices in the classifier design.- Outlier detection using classifier instability.- Distribution free decomposition of multivariate data.- Classifier conditional posterior probabilities.- Editing prototypes in the finite sample size case using alternative neighborhoods.- Image classification using a stochastic model that reflects the internal structure of mixels.- Nearest neighbors in random subspaces.- A model for non-stationary time series analysis with clustering methods.- Robust cluster analysis via mixtures of multivariate t-distributions.- Consistent set estimation in k-dimensions : An efficient approach.- A statistical theory of shape.- Accurate detection and characterization of corner points using circular statistics and fuzzy clustering.- An approximate nearest neighbours search algorithm based on the Extended General Spacefilling Curves Heuristic.- A pretopological approach for pattern classification with reject options.- Optimizing the error/reject trade-off for a multi-expert system using the Bayesian combining rule.- Optimum decision rules in pattern recognition.- On unifying probabilistic/fuzzy and possibilistic rejection-based classifiers.- Rejection versus error in a multiple experts environment.- Distance rejection in the context of electric power system security assessment based on automatic learning.- On virtually binary nature of probabilistic neural networks.- Linear discriminant analysis for two classes via recursive neural network reduction of the class separation.- Modified minimum classification error learning and its application to neural networks.- Applying voting to segmentation of MR images.- Segmentation of natural images using hierarchical and syntactic methods.- Nonlinear variance measures in image data.- Non-linear mapping for feature extraction.- MDL-based selection of the number of components in mixture models for pattern classification.- Stepwise selection of perceptual texture features.- Pattern classification with noisy features.- Features for the classification of marine microfossils.- A statistical clustering model and algorithm.- BANG-Clustering: A novel grid-clustering algorithm for huge data sets.- Set partition principles revisited.- Pattern classification based on local learning.- Comparison of different methods for testing the significance of classification efficiency.- Non-Gaussian stochastic model for analysis of automatic detection/recognition.- Fast median search in metric spaces.- Generalised syntactic pattern recognition as a unifying approach in image analysis.- Minimal sample size in grammatical inference a bootstrapping approach.- A statistical approach to structure and motion from image features.- A hierarchical classifier for multifont digits.- Multi-level arabic handwritten words recognition.- Mixtures of principal components Gaussians for density estimation in high dimension data spaces.- Characterization and classification of printed text in a multiscale context.- Analysis of Gabor parameters for handwritten numeral recognition by experimental design.- A new cost function for typewritten digits segmentation.- Learning parameters of Gibbs random fields using unconditional and conditional MLE of potentials.- A nonparametric data mapping technique for active initialization of the multilayer perceptron.- Pattern recognition learning applied to stereovision matching.- Human verification using 3D-gray-scale face image.- Subject-based modular eigenspace scheme for face recognition.- Unsupervised texture segmentation.- Invisible modification of the palette color image enhancing lossless compression.- A statistical model for an automatic procedure to compress a word transcription dictionary.
| Erscheint lt. Verlag | 29.7.1998 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | XLIV, 1050 p. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1326 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | 3D • algorithms • classification • cluster analysis • computer vision • Data Analysis • fuzzy • Genetic algorithms • Graphics Recognition • Hardcover, Softcover / Informatik, EDV/Informatik • HC/Informatik, EDV/Informatik • Image Analysis • Image Ananalysis • Mustererkennung • Object recognition • pattern recognition • Semantics • Textur |
| ISBN-10 | 3-540-64858-5 / 3540648585 |
| ISBN-13 | 978-3-540-64858-1 / 9783540648581 |
| Zustand | Neuware |
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