A New Method for Rotation Free Method for Online Unconstrained Handwritten Chinese Word Recognition: A Holistic Approach
Kai Ding, Lianwen Jin, Xue Gao · 2009
Most online handwriting word recognition (HWR) approaches proceed by segmenting words into isolate characters which are recognized separately. Inspired by results in cognitive psychology, holistic word recognition approaches provides another effective way to deal the problem of HWR. In this paper, we propose a new method for rotation free online unconstrained Chinese word recognition through a holistic approach. By a gravity center balancing skew detection and correction method, the rotation ranging from 0deg to 360deg of a Chinese handwritten word can be detected. Through the process of preprocessing, feature extraction using elastic meshing technique and classification, the handwritten words with characters even connected or partially overlapped can be recognized through a holistic approach. Experiments were performed on 8888 categories of 1,137,664 unconstrained handwritten Chinese word samples. Experimental results for randomly rotated unconstrained cursive handwritten Chinese word data demonstrated that the proposed method can achieve about 96.58% recognition accuracy.