针对增强现实识别注册的精度易受纹理影响且缺少以文字为识别目标的问题,提出了一种基于文字特征的识别注册方法。在模板图像处理中,将降采样与2幂次采样相结合构建多尺度金字塔,实现尺度不变性;采用基于快速视网膜特征改进的算法提取文字特征点,实现基于文字特征的增强现实系统。实验结果表明:所提算法能较准确地提取图像文字特征点,减弱了纹理对精度的影响,适用于对文本图像的识别注册。基于此方法实现的增强现实系统在不同尺度角度和目标被部分遮挡的情况下仍可以较准确地进行识别注册。

A text feature-based recognition registration method is proposed to address the problems that the accuracy of the augmented reality recognition registration is prone to be affected by textures and that there is lack of text-based recognition targets. In template imaging processing, two sampling methods,i.e., downsampling and 2 power-based sampling,are combined to construct a multi-scale pyramid, achieving scale invariance. The text feature points are extracted based on an improved algorithm that uses fast retina keypoint (FREAK). Finally, the augmented reality system based on text features is realized. The experimental results show that the proposed algorithm can extract text feature points accurately and reduce the effect of the texture on accuracy, and it is applicable to the recognition registration for text images. Further, the augmented reality system based on the improved method can realize recognition registration in the situation that the target is partially obscured under different scales.