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Method for identifying mechanical damage area of corn ear

A corn ear and mechanical damage technology, applied in the field of pattern recognition, can solve the problem of low recognition accuracy and achieve the effect of improving speed and accuracy

Inactive Publication Date: 2018-10-16
CHINA AGRI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the shortcomings of the low recognition accuracy existing in the existing corn ear mechanical damage area identification technology, the present invention provides a method for identifying the corn ear mechanical damage area

Method used

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  • Method for identifying mechanical damage area of corn ear

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Embodiment Construction

[0017] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0018] figure 1 It is a flow chart of a method for identifying mechanically damaged areas of corn ears according to an embodiment of the present invention. Such as figure 1 Shown, a kind of corn ear mechanical damage area recognition method comprises: step S1, the corn ear image is divided into image small block, obtains corn ear image small block data set; Step S2, according to the image small block data set The normalized features are determined by using the support vector machine to determine the small pieces of the candidate area; step S3, using the convolutional neural network model to determine the mechanically damaged area in the candidate area.

[0019] Before i...

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Abstract

The invention provides a method for identifying a mechanical damage area of a corn ear. The method comprises the following steps of: S1, dividing a corn ear image into image patches, obtaining a cornear image patch data set; S2, according to the normalized feature of each image patch in the image patch data set, determining a candidate region patch by using a support vector machine; and S3, usinga convolutional neural network model to determine the mechanical damage region in the candidate region patches. According to the method for identifying the mechanical damage area of the corn ear, selecting the candidate region in the corn ear image by using the support vector machine, further identifying by the convolutional neural network model, and can quickly and accurately identify the mechanical damage region of the corn ear; therefor, the speed and accuracy of the identification of the mechanical damage area of the corn ear can be improved, and the needs of corn testing can be meet.

Description

technical field [0001] The invention relates to the technical field of pattern recognition, and more particularly, relates to a method for recognizing a mechanically damaged region of corn ears. Background technique [0002] At present, the identification of mechanically damaged areas of corn ears is the basic project in the detection of corn ear defects. Maize ears will inevitably be mechanically damaged during mechanical harvesting and transportation. Manually judging the mechanical damage of corn ears is a heavy workload and difficult to quantify. Generally, only the classification of mechanical damage can be given. [0003] The use of computer vision to identify the mechanically damaged area of ​​corn ears can well replace manual labor and effectively improve the identification efficiency. The main problem of automatic recognition of mechanically damaged areas in corn ear images based on machine learning is that they are easily affected by light, and high light areas ar...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06K9/62G01N21/88
CPCG06T7/0002G01N21/8851G01N2021/8887G06T2207/20081G06T2207/20084G06T2207/20076G06F18/2411G06F18/214
Inventor 马钦张秦川朱德海张晓东崔雪莲杨玲
Owner CHINA AGRI UNIV
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