A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
Fundamentals of speech recognition
Fundamentals of speech recognition
A survey of moment-based techniques for unoccluded object representation and recognition
CVGIP: Graphical Models and Image Processing
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Document Image Decoding Using Markov Source Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Musical Score Recognition Using Probabilistic Reasoning
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Adaptive optical music recognition
Adaptive optical music recognition
The interface between phrasal and functional constraints
Computational Linguistics
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In this paper, we illustrate the use of a novel probabilistic framework for document analysis on typical problems of document layout analysis and graphics recognition. Our system uses an explicit descriptive model of the document class to find the most likely interpretation of a scanned document image. In contrast to the traditional pipeline architecture, our system carries out all stages of the analysis with a single inference engine, allowing for an end-to-end propagation of the uncertainty.