基于BP神经网络的触摸屏校准算法

Calibration algorithm of touch screen based on BP neural network

由于触摸屏的密度不一致,采用简单线性转换限制了校准精度的提高。为了获得更高的校准精度,提出了基于BP神经网络的电阻型触摸屏校准方法,构建了神经网络模型,并利用BP算法的非线性隐射能力对触摸屏标定数据进行了输入-输出的非线性逼近。仿真实验结果表明,与两点比例校准相比该校准方法在校准精度上大约提高了3倍,明显优于同类算法。

Because of the density is different on the touch screen, the simple calibration algorithm affects the calibration precision directly. Aiming at improving the calibration precision, a method of calibration based on BP neural network was proposed. The neural network model was constructed. The nonlinear reflecting capability of BP neural network was applied to approach the I/O characteristic curve. Simulation results show that the proposed method improves the calibration precision of about 3 times than congener calibration algorithms.