Grabbing point positioning method for naturally placed grape bunches on basis of machine vision

A technology of machine vision and point positioning, which is applied in the direction of neural learning methods, instruments, harvesters, etc., can solve the problems of various shapes and irregular distribution of grape bunches, achieve accurate and fast extraction, and improve the effect of image quality

Inactive Publication Date: 2018-10-19
JIANGSU UNIV
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  • Application Information

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Problems solved by technology

Compared with the grape bunches in the hanging growth state in the natural environment, due to the randomness of placement, the main fruit stem where the grabbing point is located has no shape and position constraints, and the

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  • Grabbing point positioning method for naturally placed grape bunches on basis of machine vision
  • Grabbing point positioning method for naturally placed grape bunches on basis of machine vision
  • Grabbing point positioning method for naturally placed grape bunches on basis of machine vision

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Embodiment

[0078] The present invention emphatically proposes a grape bunch grasping point positioning method based on machine vision based on multi-feature and gradient direction contour analysis, which solves the problem that the main fruit stalk of the grape bunch naturally placed has no shape and position constraints, and it is difficult to directly identify the main fruit in the image through the feature threshold. At the same time, the extraction accuracy and speed of the main fruit stem are greatly affected by the size of the feature and the coupling between features, and it is difficult to directly perform geometric fitting and diameter calculation on the outline of the main fruit stem. question.

[0079] Specific embodiments are described by taking the string fruit sorting robot developed by our research group as an example, and white rosa grapes as the grasping objects. Its specific implementation is as follows:

[0080] 1. Image acquisition and preprocessing based on binocula...

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Abstract

The invention discloses a grabbing point positioning method for naturally placed grape bunches on the basis of machine vision. According to the space grabbing range, grabbing precision and speed and other requirements of a bunch-type fruit sorting robot, a hardware platform for acquiring grape bunch images is constructed first; the colored images of the naturally placed grape bunches on the basisof machine vision are obtained and preprocessed to obtain binary images of the grape bunches containing main fruit stem regions, secondary fruit stem regions, fruit stalk regions and other regions; multi-dimensional feature vectors of the grape bunches and a BP neural network are constructed to extract the main fruit stem regions, and gradient direction contour analysis is adopted for locating grabbing points; finally, on the basis of binocular vision calibration parameters, image coordinates of the grabbing points are converted into spatial three-dimensional coordinate points to obtain spatial three-dimensional coordinates of the grabbing points of the naturally placed grape bunches, so that the robot automatically grasps the naturally placed grape bunches.

Description

technical field [0001] The invention relates to the field of machine vision, in particular to a grasping point positioning method for naturally placed grape bunches based on machine vision and image processing, which is used for automatic sorting by robots. Background technique [0002] In recent years, my country's fruit production has grown rapidly, and traditional manual sorting methods have been difficult to meet the needs of modern agricultural production. Automatic fruit sorting based on robotic technology is of great importance to the automation, scale, and precision development of agricultural production and agricultural product processing. significance. In the robot-based automatic fruit sorting process, the accurate positioning of the grasping point is the prerequisite for the robot to achieve accurate, fast and non-destructive grasping control. Due to the advantages of non-contact, strong applicability, and high cost performance, machine vision is suitable for sol...

Claims

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Application Information

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IPC IPC(8): A01D46/28B25J9/16G06K9/32G06K9/34G06N3/08
CPCA01D46/28G06N3/084B25J9/16B25J9/1697G06V10/255G06V10/267
Inventor 高国琴张千
Owner JIANGSU UNIV
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