DISCRETE DISTANCE AND SIMILARITY MEASURES FOR PATTERN CANDIDATE SELECTION

被引：3
|
作者：
LI, X [1 ]
HALL, NS [1 ]
HUMPHREYS, GW [1 ]
机构：
[1] UNIV BIRMINGHAM,SCH PSYCHOL SCI,BIRMINGHAM B15 2TT,W MIDLANDS,ENGLAND
来源：
PATTERN RECOGNITION | 1993年 / 26卷 / 06期
关键词：
PATTERN PRIMITIVE; REPEATABLE COMBINATION; SET FAMILY; DISTANCE SPACE; SIMILARITY MEASURE;
D O I：
10.1016/0031-3203(93)90050-7
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Within the area of pattern recognition research, there are many examples where pattern families are decomposed into or composed from a set of basic elements. Regardless of their decomposition/composition order, each pattern within such a family can be considered as a repeatable combination of pattern primitives, and a discrete distance space and a corresponding similarity measure to facilitate the pattern recognition process can be defined. The definitions and properties relevant to the above discrete distance and similarity measures are presented. Both principles and an implementation method for pattern candidate selection within the discrete distance space are discussed.
引用
收藏
页码：843 / 851
页数：9
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