Development of Rapid Detection Algorithm of Straw Coverage Rate Based on Color Spatial Distance Gray and K-means Method
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    Abstract:

    Straw coverage rate is one of the most important evaluation indexes for conservation tillage. In view of the difficult problem of different shapes of straw and difficult recognition of the fine straw, a straw coverage rate detection algorithm based on K-means and color space distance gray-scale method was proposed to solve the problem of different straw shapes and difficult identification of broken straw. The color spatial distance method was used to preprocess the straw image. The classification recognition of the straw and soil background was realized based on the K-means algorithm. After the identified images were processed by using the mathematical morphology method, the coverage rate of the straw image was calculated. In 2022, the field experiment was conducted to verify the algorithm on 220 corn straw images collected from Beijing Xiaotangshan National Precision Agriculture Research Demonstration Base. The experimental results showed that the recognition accuracy of low straw coverage rate (0~30%) was 90%. And the recognition accuracy of medium straw coverage rate (30%~60%) was 88%. For the high straw coverage rate (more than 60%), the recognition accuracy reached 86%. The accuracy rate of overall identification grading reached 9818%. The straw coverage rate detection algorithm based on K-means and color spatial distance gray provided a rapid detection method and means for conservation tillage evaluation.

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History
  • Received:June 26,2023
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  • Online: August 27,2023
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