Chinese-Chess Image Recognition by using Feature Comparison Techniques

In this paper, we develop a feature comparison method for the Chinese-chess object by using the features comparison based on input image and database. Features are generated by calculating the distance between the contour of the character and the centre of the chess object. In this paper, the noise filter, object extraction, normalization, feature calculation (FC) and maximum energy slop (MES) method are used to achieve robust Chinese-chess recognition. There are two advantages when compared with other methods. 1) Our method is robust against the 40 incline degree attacks. 2) Our method can resist the 20% pepper and salt noise attacks. In order to demonstrate the effectiveness of the proposed scheme, simulations under all kinds of various conditions were conducted. The experimental results show that our proposed scheme can exactly identify chess images at 100% of accuracy under less than 20% noise added and 40 degree incline test environment condition.