Forest pest monitoring image analysis based on fuzzy pixel clustering and watershed approaches

Author:

Xu Yunjian1,Guo Aiyin2

Affiliation:

1. School of Intelligent Engineering, Guangdong AIB Polytechnic, Guangzhou, China

2. School of Internet of Things Application Technology, Guangdong AIB Polytechnic, Guangzhou, China

Abstract

The orthophotos of Pinus tabulaeformis and seabuckthorn were collected by UAV, these images were used as test images, and the performance of six image segmentation algorithms were qualitatively analyzed and quantitatively compared such as fuzzy pixel clustering and watershed algorithms. The error rate, relative final measurement accuracy, and running time are used as evaluation criteria. The experimental results show that the segmentation algorithms’ performance of the affected forest image is closely related to the image-capturing height and noise. Finally, the guiding suggestions for the application of the orthophoto segmentation algorithm are given from unmanned aerial vehicles in the affected forest area.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference26 articles.

1. Study on Prevention and Control of Forest Diseases and Insect Pests and Forest Management Technology;Zhao;Journal of Agricultural Catastrophology,2022

2. Crop Protection and Environment: Sustainable Control Measures of Pests and Diseases;Brotodjojo;2022 IOP Conf. Ser.: Earth Environ Sci

3. Hyperspectral Data and WebGIS Based Monitoring System for Forest Pests and Diseases;Pan;World Forestry Research,2015

4. Application of electronic inspection technology in the forest pest management;Ren;Forest Pest and Disease,2014

5. WebGIS for Monitoring Sudden Oak Death in coastal California;Nina Kelly;Computers, Environment and Urban Systems,2003

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