用于视觉导航自动车辆的统计数字识别方法

通过对图像特征选择不同方法的分析,考虑到图像的全局特征更易被检测到,而且更不易受到噪声和较小的局部失真影响,提出了以全局特征为立足点,即从图像的总体出发,采用图像的灰度均值为主要特征量的特征选择与提取方法。在此基础上,全面分析了数字分块的机理,并采用投影的方法得到了10个数字的特征值。为实现对数字的快速识别,对得到的数字投影值采用了方向特征的处理方法。试验结果表明:有噪声的情况下,通过利用统计原理获得数字特征值能够实现对数字的快速、准确识别,该方法具有较好的抗干扰能力。

Statistical numerical recognition for vision navigated vehicle

Different approaches to the image feature selection were summarized. In view of the image global features are more likely to be detected and not liable to be disturbed by noise and local distortion, an approach to the image feature selection and extraction based on the global feature was proposed. The mean gray-scale of the image was taken as the major feature value. The image was divided into several blocks, the feature values expressed by 10 numbers were obtained by means of horizontal and vertical projection. To realize the quick real-time recognition of the number, the values of the feature numbers after projection were processed in accordance with the original projective direction. The experimental results show that the numbers in an image with moderate noise can be accurately and quickly recognized by the statistical approach which has a good anti-jamming ability.