Sketched symbol recognition using zernike moments
Heloise Hse, A. Richard Newton · 2004
In this paper, we present an on-line recognition method for hand-sketched symbols. The method is independent of stroke-order,-number, and-direction, as well as invariant to rotation, scaling, and translation of symbols. Zernike moment descriptors are used to represent symbols and three different classification techniques are compared: Support Vector Machines (SVM), Minimum Mean Distance (MMD), and Nearest Neighbor (NN). We have obtained 97 % accuracy rate on a dataset consisting of 7,410 sketched symbols using Zernike moment features and a SVM classifier. This method has been implemented in a software recognition package, HHreco [7]. 1.