Crop Detection Using Images and the Uniform Spacing in Crop Positions

Abstract

Crop detection is important for automatic weeding. A previous study achieved crop detection by detecting plant blobs in crop rows and by classifying them as crop or weed using k-means. However, this method was not robust to the amount and shape variation of the weed. In this paper, we propose a crop detection method that uses the uniform spacing in crop positions to address the problem encountered by the previous method. The classification results of the previous method are updated such that plants with uniform spacings are classified as crop. Experiments with artificial and real weeds validate the effectiveness of the proposed method.