Sugarcane image stitching under transverse transport based on improved SURF algorithm

Authors

  • Deqiang Zhou 1. School of Intelligent Manufacturing, Jiangnan University, Wuxi 214401, China
  • Jiahao Zhu 1. School of Intelligent Manufacturing, Jiangnan University, Wuxi 214401, China
  • Wenbo Zhao 1. School of Intelligent Manufacturing, Jiangnan University, Wuxi 214401, China
  • Fengguang He 2. Agro-Machinery Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang 524000, China
  • Lijiao Wei 2. Agro-Machinery Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang 524000, China
  • Ganran Deng 2. Agro-Machinery Research Institute, Chinese Academy of Tropical Agricultural Sciences, Zhanjiang 524000, China

DOI:

https://doi.org/10.25165/ijabe.v18i5.9058

Keywords:

sugarcane image, image stitching, image registration, feature extraction, feature matching, SURF

Abstract

This paper proposes a sugarcane image stitching algorithm based on an improved SURF method to capture highquality, wide-field images of complete sugarcane stalks. To enhance registration accuracy, artificial markers are introduced into the background, helping to address the challenges posed by the smooth surface of sugarcane and low feature point matching precision. Additionally, a mesh segmentation technique combined with an enhanced SURF algorithm is used for feature extraction, which tackles issues such as uneven feature distribution and slow processing speed caused by global image feature extraction. A double screening registration method is also proposed to further improve the accuracy of image mosaicing. To reduce stitching gaps, an image fusion technique based on the optimal suture line is employed. Experimental results show that the algorithm has an average runtime of about 2900 ms, slightly longer than the ORB algorithm at 2000 ms but significantly faster than the original SURF at 4200 ms. In terms of stitching quality, the average image information entropy is 6.34, which is higher than both the SURF (6.325) and ORB (6.075) algorithms, indicating better image quality. Keywords: sugarcane image, image stitching, image registration, feature extraction, feature matching, SURF DOI: 10.25165/j.ijabe.20251805.9058 Citation: Zhou D Q, Zhu J H, Zhao W B, He F G, Wei L J, Deng G R. Sugarcane image stitching under transverse transport based on improved SURF algorithm. Int J Agric & Biol Eng, 2025; 18(5): 278–286.

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Published

2025-10-27

How to Cite

Zhou, D., Zhu, J., Zhao, W., He, F., Wei, L., & Deng, G. (2025). Sugarcane image stitching under transverse transport based on improved SURF algorithm. International Journal of Agricultural and Biological Engineering, 18(5), 278–286. https://doi.org/10.25165/ijabe.v18i5.9058

Issue

Vol. 18 No. 5 (2025): IJABE

Section

Information Technology, Sensors and Control Systems

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