Image detection and verification of visual navigation route during cotton field management period

Abstract

In order to meet the actual operation demand of visual navigation during cotton field management period, image detection algorithm of visual navigation route during this period was investigated in this research. Firstly, for the operation images under natural environment, the approach of color component difference, which is applicable for cotton field management, was adopted to extract the target characteristics of different regions inside and outside cotton field. Secondly, the median filtering method was employed to eliminate noise in the images and realize smoothing process of the images. Then, according to the regional vertical cumulative distribution graph of the images, the boundary characteristic of the cotton seedling region was obtained and the central position of the cotton seedling row was determined. Finally, the detection of the candidate points cluster was realized, and the navigation route was extracted by Hough transformation passing the known point. The testing results showed that the algorithms could rapidly and accurately detect the navigation route during cotton field management period. And the average processing time periods for each frame image at the emergence, strong seedling, budding and blooming stages were 41.43 ms, 67.83 ms, 68.80 ms and 74.05 ms, respectively. The detection has the advantage of high accuracy, strong robustness and fast speed, and is simultaneously less vulnerable to interference from external environment, which satisfies the practical operation requirements of cotton field management machinery. Keywords: visual navigation, route detection, Hough transformation passing the known point, cotton field management period DOI: 10.25165/j.ijabe.20181106.3976 Citation: Li J B, Zhu R G, Chen B Q. Image detection and verification of visual navigation route during cotton field management period. Int J Agric & Biol Eng, 2018; 11(6): 159–165.