Automatic clustering method

Image analysis – Histogram processing – For setting a threshold

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382 14, G06K 970

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active

053295960

ABSTRACT:
An automatic pattern recognition method has a short processing time, can be applied to nonlinear separation problems, and can perform similarity calculations. The method: Divides a plurality of sample data of known categories into a plurality of classes; When the sample data in a divided class is not all in the same category, repeats dividing the sample data into subclasses until sample data in a subclass has only one category; Expresses the relationship between classes and subclasses in a tree-structure representation and determines the standard pattern for each class and subclass from the sample data contained there; and Checks which of the tree-structured classes input data of unknown category is nearest, by calculating the distance to the standard pattern of each class, and then, when the class has subclasses, performs a similar check until the lowest-level subclass is reached to determine the subclass the input data is closest to. The category of the lowest-level subclass is taken as the category of the input data.

REFERENCES:
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patent: 4773099 (1988-09-01), Bokser
patent: 4975975 (1990-12-01), Filipski
patent: 5075896 (1991-12-01), Wilcox et al.
Rumelhart, David E., et al., Parallel Distributed Processing, vol. 1, Chapter 8, The MIT Press, Cambridge, Massachusetts Feb. 2, 1988.
Artificial Intelligence Handbook, Published by Hon, Pattern Matching, p. 324, Compiled by The Artificial Intelligence Association of Japan.

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