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Corn ear damage detection method

A corn ear and damage detection technology, applied in image data processing, image enhancement, instruments, etc., can solve problems such as corn ear damage, achieve the effects of reduced model parameters, high detection accuracy, and improved generalization ability

Active Publication Date: 2019-07-26
CHINESE ACAD OF AGRI MECHANIZATION SCI
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AI Technical Summary

Problems solved by technology

[0008] The technical problem to be solved by the present invention is to provide a method for detecting corn ear damage based on deep learning, which is used to solve the problem of real-time detection of corn ear damage in the complex scene of machine harvesting

Method used

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Embodiment Construction

[0053] Below in conjunction with accompanying drawing, structural principle and working principle of the present invention are specifically described:

[0054] The corn ear damage detection method of the present invention comprises the following steps:

[0055] Step S100, obtain the training set pictures and their labels, and use the labels to mark the training set pictures and real pictures, the training set pictures include synthetic pictures and real pictures, and the labels include target parameters and the category of the target Number, the composite picture is synthesized from the picture taken at the elevator of the corn combine harvester and the picture of the damaged corn ear, and the target parameters include the x and y coordinate pairs of the center point of the damaged corn ear in each of the training set pictures parameters and the width and height parameters of the bounding box, the center point coordinate parameters and the width and height parameters of the bo...

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Abstract

A corn ear damage detection method comprises the following steps: obtaining a training set picture and a label thereof, labeling the training set picture and a real picture with the label, wherein thetraining set picture comprises a synthetic picture and a real picture, and the label comprises a target parameter and a number of a category to which a target belongs; modifying a network structure,re-clustering and calculating a prior frame, training a detection model by using the labeled training set pictures, and finely adjusting parameters of the detection model by using the labeled real pictures; and carrying out target detection, carrying out damage detection on the corn ear picture by using the trained detection model to predict positions and quantity of the damaged corn ears in the picture through an algorithm. The invention relates to a corn ear damage detection method based on deep learning, which is used for solving the problem of detecting corn ear damage in real time in a mechanical harvesting complex scene.

Description

technical field [0001] The invention relates to a method for detecting corn ears, in particular to a method for detecting damaged corn ears based on deep learning. Background technique [0002] With the improvement of the level of agricultural mechanization in our country, the demand for mechanized harvesting of corn is increasing. At present, corn is mainly harvested by ears. Due to the different maturity of corn when harvested by machine, the straw with high green leaf ratio and high moisture content is easy to cause various mechanical failures, and it will also cause some corn ears to be damaged. Corn ear damage will lead to problems such as a high rate of grain damage and more grain falling with the thrown objects. Therefore, real-time detection of machine-harvested corn ear damage becomes very important. The real-time situation of corn picking is processed by image detection technology and displayed on the screen, which can promptly remind the front-end operator to mak...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06N3/04
CPCG06T7/0002G06T2207/30188G06T2207/20081G06T2207/30168G06N3/045
Inventor 韩科立韩增德
Owner CHINESE ACAD OF AGRI MECHANIZATION SCI
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