Chinese Fingerspelling Recognition via Hu Moment Invariant and RBF Support Vector Machine

Gao, Ya; Wang, Ran; Xue, Chen; Gao, Yalan; Qiao, Yifei; Jia, Chengchong; Jiang, Xianwei

Sign language plays a significant role in smooth communication between the hearing-impaired and the healthy. Chinese fingerspelling is an important composition of Chinese sign language, which is suitable for denoting terminology and using as basis of gesture sign language learning. We proposed a Chinese fingerspelling recognition approach via Hu moment invariant and RBF support vector machine. Hu moment invariant was employed to extract image feature and RBF-SVM was employed to classify. Meanwhile, 10-fold across validation was introduced to avoid overfitting. Our method HMI-RBF-SVM achieved overall accuracy of 86.47 ± 1.15% and was superior to three state-of-the-art approaches.