Abstract: Due to the influence of complex working environment and artificial factors, it is easy to cause crop up over or less tillage problem when straw returning machine is working in paddy field. A new method for path detection suitable for rice, rape and wheat high crop stubble tilling environments was proposed. First the distribution characteristics of rice, rape and wheat high crop stubble images in paddy field based on RGB color model were analyzed, and rice, the color images of rape and wheat high crop stubble were converted into gray ones using custom factor combination R+G-2B; Then, the gray images of rice, rape and wheat high crop stubble were segmented from soil background by means of luminance mean texture descriptor; Next, the binary image through custom shear-binary-image algorithm was cut to remove big noise blobs in high crop stubble’s tilled area; Finally, navigation path from navigation points by using the least square method was derived. The experimental results indicated that the navigation path detection algorithm was fast and effective to obtain navigation path in rice, rape and wheat high crop stubble tilling environments with up to 96.7% of segmentation accuracy within 0.6 s of processing time. Keywords: high crop stubble, paddy field tilling, texture statistics, road navigation, vision navigation DOI: 10.3965/j.ijabe.20140704.004 Citation: Zhang T, Xia J F, Wu G, Zhai J B. Automatic navigation path detection method of high crop stubble in paddy field tilling based on machine vision. Int J Agric & Biol Eng, 2014; 7(4): 29－37.
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