Accession Number:

AD0628708

Title:

A SCHEME FOR LINEAR RECOGNITION BASED ON SELF-DETERMINED INTER-CATEGORY FEATURES.

Descriptive Note:

Technical note,

Corporate Author:

INFORMATION RESEARCH ASSOCIATES INC CAMBRIDGE MASS

Personal Author(s):

Report Date:

1965-07-15

Pagination or Media Count:

12.0

Abstract:

In a pattern recognition problem, where observations are described by a mxn grid, it is often the case that each pattern is reduced to a mask and discrimination is performed by comparing an unknown to each mask. Assignment is then determined by the closest mask. This paper discusses a preprocessing technique for feature extraction to reduce the size of the masks or to extract those mask sub-areas most pertinent for recognition. Statistical tests are applied to determine uncommon regions i.e., differences between masks. All subsequent recognition is based on and emphasizes these uncommon regions as distinguishing features. The resulting weights of this method are controlled by differences between the groups and thus cannot be separated into a characteristic set of weights from each individual group. Moreover, this method provides the freedom to elect the level of closeness that the categories must satisfy. Author

Subject Categories:

  • Statistics and Probability
  • Bionics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE