User-session-based automatic test case generation using GA
Xuan Peng, Lu Lu · International Journal of the Physical Sciences · 2011
In this paper, a new method is proposed to extract the features of a one-number Persian image in which for the final verification of the extracted features, a three-layer neural network (mesh) of Perceptron has been utilized. The method is capable of extracting some ideal features from a one-number image that are stable against rotation, movement, size change and noise. The method is examined on a database of 60000 discredited numbers, from which 40000 numbers were used in the training stage and 20000 ones were used for the experiment. The recognition percentage of 92.7% shows the great efficiency of the proposed method. Key words: Features extraction, recognition of Persian numbers, perceptron neural network, standard deviance, average angle.