A Similarity Measure for On-line Handprinted Kanji Character Recognition | Zendy

Xiaoli Li | Zendy; W. P. Dodd | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A Similarity Measure for On-line Handprinted Kanji Character Recognition

Author(s) -

Xiaoli Li,

W. P. Dodd

Publication year - 1994

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.5244/c.8.24

Subject(s) - kanji , similarity (geometry) , artificial intelligence , character (mathematics) , computer science , pattern recognition (psychology) , line (geometry) , set (abstract data type) , similarity measure , measure (data warehouse) , natural language processing , speech recognition , mathematics , chinese characters , data mining , geometry , image (mathematics) , programming language

All on-line handprinted Kanji characters consist of strokes which are the loci from pen down to pen up positions. Such strokes can be classified into predefined shape primitives and hence an on-line handprinted Kanji character can be regarded as a set of shape primitives having different direction, position and size. In this paper we define a similarity measure between characters and utilise probability judgement to estimate the similarity. Using this approach, we have obtained satisfactory results in our experiment of on-line recognition which involved 20 people as the 'writers' and covered 2,000 characters.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research