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An improved yolov3 cotton detection method under the background of complex cotton fields

A detection method, cotton field technology, applied in the direction of instrumentation, calculation, character and pattern recognition, etc., can solve the problems of few cotton detection algorithms, achieve the effect of improving the overall detection performance and enriching feature information

Active Publication Date: 2022-07-19
WUHAN INSTITUTE OF TECHNOLOGY
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Problems solved by technology

However, there are few algorithms for cotton detection
[0005] However, for the cotton target detection task in complex backgrounds, the YOLOv3 network model still needs to be improved to adapt to the task of cotton detection

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  • An improved yolov3 cotton detection method under the background of complex cotton fields
  • An improved yolov3 cotton detection method under the background of complex cotton fields
  • An improved yolov3 cotton detection method under the background of complex cotton fields

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Embodiment Construction

[0035] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be noted that the embodiments described herein are intended to facilitate the understanding of the present invention, but do not have any limiting effect on it.

[0036] The invention provides a cotton detection method based on the improved YOLOv3 complex cotton field background, such as Figure 1 to Figure 3 As shown, the method includes the following steps:

[0037] S1. The collected background images of complex cotton fields (such as Figure 4 shown) for preprocessing, and then as the input object, feature extraction is performed on the preprocessed complex cotton field background image to obtain 2x, 4x, 8x, 16x and 32x downsampling feature maps.

[0038] The preprocessing includes edge filling and size transformation, and the resolution of all collected background images of complex cotton fields is adjusted to 640×640. When the com...

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Abstract

The invention provides a cotton detection method based on the improved YOLOv3 complex cotton field background, which extracts features from the preprocessed complex cotton field background image to obtain 2 times, 4 times, 8 times, 16 times and 32 times downsampling feature maps; In the improved YOLOv3 model, a spatial pyramid convolution module is constructed in the model, and the feature map obtained after 2 times downsampling is used as the input of the spatial pyramid convolution module, and the feature map after feature enhancement is obtained. 4 times, 8 times, 16 times downsampling to enhance the feature maps P1, P2, P3; R2, R1_U, P3 are fused as the feature information of the 16 times downsampling scale, and R3, R2_U, P2 are fused as the 8 times downsampling scale. Feature information, fuse R4, R3_U, and P1 as the feature information of the 4-fold downsampling scale, and use the enhanced multi-scale feature information to predict the position information of the cotton target as the output of the improved YOLOv3 model; detection and identification.

Description

technical field [0001] The invention relates to the field of combining computer vision technology and agricultural automatic observation, in particular to an improved cotton detection method under the complex cotton field background of YOLOv3. Background technique [0002] With the development of computer vision technology, image target detection technology is widely used in various fields. At the same time, the application of computer vision technology to the agricultural field can make agriculture develop towards the direction of high quality and high yield. The automatic identification of cotton can well complete the tasks of cotton quantity statistics, cotton positioning detection, cotton yield estimation and other tasks, and provide a strong visual basis for tasks such as cotton morphology and growth analysis, automatic cotton picking, and disease and insect pest detection. In turn, it is helpful for the planning and management of cotton producing areas. However, the c...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/10G06V10/40G06V10/774G06V10/80G06K9/62
CPCG06V20/188G06V10/40G06F18/253G06F18/214
Inventor 李亚楠徐洋周于涛
Owner WUHAN INSTITUTE OF TECHNOLOGY
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