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Additional info for 43.Pattern Analysis and Machine Intelligence

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It is necessary to recognize words of text, often using lexicons and higher level linguistic and statistical context. The necessity for contextual analysis arises from the fact that it is often impossible to recognize characters and words in isolation, particularly with handwriting and degraded print. Preprocessing of character images is an important step in recognition. It is often necessary to enhance binary character images to assist the subsequent recognition process in both handwritten and machine-printed documents.

R32: R43: Headlines occupying more than one printed line are left-justified Captions are always below photographs, unless two or more photographs have a common caption Explicit boxes around blocks signify an independent unit. Blocks with different labels (photograph and text) that are not necessarily adjacent might have to be grouped together. For instance, a photograph and its accompanying caption together form a logical unit and must be linked together in the output representation. TEXT RECOGNITION AND INTERPRETATION Figure Classification.

The associative reconstruction of the vector f can be expressed in the matrix form ª f = ( f ), as derived in (29). Declarative knowledge. The question where the features come from will now be elaborated on. As long as the LTM memory limits have not been reached, the examples or rules can directly be transformed into feature vectors. Assume that the following set of propositions is to be coded: CANARY is a BIRD. BIRD is a CREATURE that FLIES. TWEETY is a CANARY. The capitalized words are the variables, or the observation units, each spanning a new dimension in the observation space.

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


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