An English Handwriting Evaluation Algorithm Based on CNNs

English handwriting evaluation is an essential part in elemental English teaching. An automatic evaluation algorithm for English handwriting quality is proposed in this paper. Generally, conventional document image processing approaches rely on hand-crafted features for capturing statistical or structural information. In contrast, we take advantage of Convolutional Neural Networks (CNNs) for extracting features from raw image pixels. The performance of this algorithm is more effective than traditional machine learning methods and the accuracy is greater than 94% in our experiment. Based on this algorithm, an intelligent English handwriting marking system is designed and it is already online.