43.Pattern Analysis and Machine Intelligence by John G. Webster (Editor)

By John G. Webster (Editor)

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Some examples are discriminant function classifiers, Bayesian classifiers, artificial neural networks (ANN), and template matchers. Discriminant function classifiers use hypersurfaces to separate the feature description of characters from different semantic classes and in the process reduce the mean-squared error. Bayesian methods seek to minimize the loss function associated with misclassification through the use of probability theory. ANNs, which are closer to theories of human perception, employ mathematical minimization techniques.

A figure block can belong to one of the following categories: half-tone picture, line-drawing (diagrams), and table. Pictures are gray-scale images and can be separated from tables and diagrams (binary images) by a histogram analysis of the gray-level distributions. Although both diagrams and tables predominantly comprise straight lines and interspersed text, the fact that the straight lines in tables run only vertically and horizontally can be used to advantage. Analysis of the Hough transform accumulator array is used to separate tables from diagrams.

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