A Study on Handwritten Character Recognition

• Main Authors: Chu-Chong Hoi, 許主聰
• Other Authors: 劉長遠
• Format: Others
• Language: en_US
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/04065851585956727358

碩士 === 臺灣大學 === 資訊工程學研究所 === 98 === There are many applications for handwritten character recognition, such as signature verification, handwritten address recognition, pen-based input method used in PDA etc. In this thesis, we just consider offline character recognition because it is the basic building block of many complicate handwriting recognition system. We compare four techniques for handwritten recognition. They are PCA, LDA, NMF and ICA. The result shows that PCA has the highest accuracy. LDA has the lowest accuracy due to small training data set. The difference of performance between ICA and PCA is small. NMF only need smaller number of basis images within each class when considering class information.