An efficient algorithm for detecting shortage of soybean seedlings using RGB images captured by UAVs

He Li; Yigao Xu; Yiqiu Zhao; Li Ding; Changle Guo; Zishang Yang

doi:10.1117/12.2684259

1 August 2023 An efficient algorithm for detecting shortage of soybean seedlings using RGB images captured by UAVs

He Li, Yigao Xu, Yiqiu Zhao, Li Ding, Changle Guo, Zishang Yang

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127542C (2023) https://doi.org/10.1117/12.2684259
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

It is necessary to develop an efficient method for the detection of seedlings shortage and breaking rows of soybean. In this paper, we design an efficient detection algorithm for the shortage of soybean seedlings using RGB images captured by UAVs. Then we apply a series of techniques for detecting the centerline of the crop row. Otsu-based binarization segmentation is utilized to segment the vegetation canopy from the image, thereby supporting the further analysis of crucial field indicators. Finally, we perform local projection segmentation of crop rows using the projection integral curve segmentation algorithm, which can detect the position of the missing seedlings in the crop rows. The results show that the accuracy of crop rows detection achieves 93.9%; the accuracy of crop rows detection under different planting modes and the UAV flight heights achieves more than 92%, which indicates the robustness of the detection algorithm. The detection results of this method have obtained a good performance inaccuracy. From the average time of crop rows detection is 0.31s, the detection speed and efficiency are also guaranteed. The analysis shows that the X coordinate of variance detection of line breaking position coordinate is P=0.97125, and the Y is P=0.13156. There is reason to believe that the test results are good.

Citation Download Citation

He Li, Yigao Xu, Yiqiu Zhao, Li Ding, Changle Guo, and Zishang Yang "An efficient algorithm for detecting shortage of soybean seedlings using RGB images captured by UAVs", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127542C (1 August 2023); https://doi.org/10.1117/12.2684259

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KEYWORDS

Image segmentation

Unmanned aerial vehicles

Vegetation

Tunable filters

Image filtering

Detection and tracking algorithms

Image processing algorithms and systems

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