Bursaphelenchus xylophilus disease image recognition and detection method and device

Abstract

The invention belongs to the technical field of pine wood nematode disease image recognition and detection, and particularly relates to a pine wood nematode disease image recognition and detection method and a pine wood nematode disease image recognition and detection device, pine wood nematode disease is detected by setting a deep learning target detection technology, the recognition efficiency of diseased wood can be effectively improved, and the detection precision is relatively high; the image intelligent identification and positioning method adopts a unified discrimination standard, so the coverage rate of identification results is effectively improved, and the generalization ability is high. According to the above advantages, the pine wood nematode disease image identification and detection method can timely discover infected pine trees and determine the distribution condition of the pine trees, effectively monitor the development trend of pine wood nematode disease epidemic situations, and provide timely and accurate information for pine forest management personnel and forest protection personnel.

Description

technical field [0001] The invention belongs to the technical field of image recognition and detection of pine wood nematode disease, and in particular relates to a method and device for image recognition and detection of pine wood nematode disease. Background technique [0002] The identification of pine wood nematode diseased trees is affected by noise, light, season and many other factors. The identification includes missed and misjudgment of discolored trees. Misjudgments such as the discoloration canopy being blocked, the diameter of the discoloration canopy being too small, and poor image splicing caused the discoloration trees in some areas to be difficult to distinguish; misjudgments such as other ground objects such as yellow shrubs, bare soil, dead grass or Dead trees that have been felled but not sealed in bags are judged as discolored trees. This requires the recognition algorithm to overcome complex and multi-scene interference to improve the recognition accura...

AI Technical Summary

Problems solved by technology

At present, the image extraction of discolored pine trees is still at the level of visual interpretation, and the work plan of completely relying on manual visual interpretation of discolored pine trees is inefficient and highly subjective

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