A New Combination Method Based on Different Representation of Data

This paper proposes a new classification method for Farsi handwritten word recognition using gradient and gradient based features. The extracted feature vectors were classified using two Multi Layer Perceptron networks as basic experts, and one Radial Basis Function was applied to choose the best expert. The experiments were performed using the Iranshahr dataset. This dataset consists of 780 samples of 30 city names of Iran out of which, 600 samples were used to train the network and 180 samples to test it. A set of experiments were conducted to compare proposed method with some other combination rules. Results show that the proposed method achieved 91.11% recognition rate.