Vision-based agricultural vehicle navigation has become a popular research area of automated guidance, however, crop row detection in high weeds field is still a challenging topic. An image segmentation method mainly based on frequency and color information is proposed to remove weeds. The algorithm is based on total frequency parameters, more total crop frequency, alternation regular of crop rows, Otsu method and color model transformation. The total frequency parameters are obtained from wavelet multi-resolution decomposition. The least square method is used in fitting straight line to detect the crop rows. Experiments show that the algorithm can effectively overcome the high weeds. The average processing time of a single pixels image is 132 ms.
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