Handwritten Numeral Recognition Based on Simplified Feature Extraction, Structural Classification and Fuzzy Memberships
學年 92
學期 2
出版（發表）日期 2004-05-01
作品名稱 Handwritten Numeral Recognition Based on Simplified Feature Extraction, Structural Classification and Fuzzy Memberships
作品名稱（其他語言）
著者 Jou, Chi-chang; Lee, Hung-chang
單位 淡江大學資訊管理學系
出版者
著錄名稱、卷期、頁數 Lecture notes in artificial intelligence 3029, pp.372-381
摘要 Structural classification recognizes handwritten numerals by extracting geometric primitives that characterize each image. We propose a handwritten numeral recognition system based on simplified feature extraction, structural classification and fuzzy memberships, with the intention to find a small set of primitives without sacrificing the recognition rate. For each image, we first perform simplified preprocessing of smoothing and thinning to obtain a skeleton. For each skeleton, the following feature points are detected: terminal, intersection, and directional. We then extract the following primitives for each skeleton: loop, horizontal, vertical, leftward curve, and rightward curve. A fuzzy S-function is used as the membership function to estimate the likelihood of these primitives being close to the vertical boundary of the image. A tree-like classifier based on the extracted feature points, primitives and fuzzy memberships is then applied to recognize the numerals. Handwritten numerals in NIST Special Database 19 are recognized with correct rate between 87.33% and 88.72%.
關鍵字
語言 en
ISSN
期刊性質 國內
收錄於
產學合作
通訊作者
審稿制度 否
國別 TWN
公開徵稿
出版型式 ,電子版
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