Real-time identification method of hickory nut fruits in image based on machine vision

A technology of machine vision and recognition methods, applied in image enhancement, image analysis, image data processing and other directions, can solve problems such as unsystematic research

Active Publication Date: 2021-03-16
ZHEJIANG UNIVERSITY OF SCIENCE AND TECHNOLOGY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although there are many research results at home and abroad, how to improve the picking robot's ability to perceive the hickory fruit growth environment and ensure high accuracy of target recognition on the basis of only using visible light sensors, improve the robustness and real-time performance of the algorithm No systematic studies

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  • Real-time identification method of hickory nut fruits in image based on machine vision
  • Real-time identification method of hickory nut fruits in image based on machine vision
  • Real-time identification method of hickory nut fruits in image based on machine vision

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Embodiment Construction

[0028] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0029] Such as figure 1 Shown, the present invention comprises the following steps:

[0030] 1) Perform down-sampling processing on the image collected by the camera, reduce the image resolution, and obtain the down-sampled image; the sampling device is a mountain dog A8 motion camera, and the resolution of the original image is 8000*6000. In order to reduce the processing time of the computer, use ACDsee The software changes the resolution of the original image to 4000*3000.

[0031] 2) Smooth and denoise the downsampled image to obtain a denoised image;

[0032] In a specific implementation, Gaussian filtering is used to perform smoothing and denoising processing on the down-sampled image...

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Abstract

The invention discloses a target recognition method of a hickory nut picking robot based on machine vision. The method comprises the following steps: down-sampling an original image to obtain a down-sampled image; carrying out smooth denoising processing on the down-sampled image to obtain a denoised image; converting the denoised image in different color spaces, selecting and extracting a featureimage component with obvious target features, and acquiring a first binary image after threshold segmentation; processing the denoised image according to a color threshold range to obtain a second binary image; and performing morphological processing on the first binary image and the second binary image, and then taking a public area of the two images, wherein the public area is a hickory nut fruit recognized by the picking robot. According to the method, the classification rate of hickory nut target images is improved, and the method has good classification robustness and accuracy.

Description

technical field [0001] The invention relates to a target recognition method of a pecan picking robot, in particular to a machine vision-based real-time recognition method of a pecan fruit in an image. Background technique [0002] For the automated hickory picker, identifying the operating object is the key problem that the picking robot needs to solve. On the one hand, naturally growing hickory nuts have individual differences, and their physical forms such as size, shape, and color are different, and change with time; on the other hand, the interference of complex backgrounds such as the occlusion of hickory fruit branches and leaves increases It reduces the difficulty of identifying the work object. Therefore, in order for the picking machine to accurately identify the work object from the complex operating environment, the picking machine must be supported by powerful analysis and recognition algorithms. Color information is the most commonly used feature to distinguis...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/40G06K9/44G06K9/46G06T7/11G06T7/136
CPCG06T7/11G06T7/136G06T2207/10024G06T2207/20024G06T2207/30188G06V20/10G06V10/34G06V10/30G06V10/56
Inventor 周扬陈梓濠张铮陈正伟施秧王斐宋起文陈军勇刘喜昂陶红卫周武杰王新华程志刚吴元锋
Owner ZHEJIANG UNIVERSITY OF SCIENCE AND TECHNOLOGY
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