车载摄像平台序列图像快速拼接方法

Fast sequence images mosaic based on vehicle-borne camera platform

  • 摘要: 针对车载摄像平台序列图像拼接中存在畸变、数据量大的问题,提出一种车载摄像平台序列图像快速拼接方法。首先对图像进行预处理来消除畸变的影响,然后对图像检测SURF特征点,定义特征点匹配率作为图像的相似性度量,根据特征点匹配率提取关键帧,再采用改进的配准策略得到全局配准模型,避免了配准误差的累积,最后采用一种最大值融合法得到序列图像的拼接图。实验结果表明:该方法具有较强的鲁棒性、更为快速。

     

    Abstract: Distortion and mass data are difficult problems in image sequence mosaic on vehicle-borne camera platform. A fast image sequence mosaic method was proposed for solving the problems. Firstly, the distortion was removed after image preprocessing. Secondly, the speeded up robust features (SURF) were extracted from preprocessing images and the features were matched. The rate of feature matching was defined as a similarity measure of frames to extract key frames. Then, by using the improved image registration method without accumulated error, a global model was established. Finally, the image sequence mosaic was obtained through image fusion of the maximum. The experimental results show that the method is robust and fast.

     

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