scholarly journals THE DESIGN OF GROUND AIR DUAL PURPOSE AGRICULTURAL INFORMATION ACQUISITION ROBOT

2020 ◽  
pp. 259-268
Author(s):  
Qinlan Li
Keyword(s):  
Machine Vision ◽  
Information Acquisition ◽  
Vision System ◽  
Control Group ◽  
Machine Vision System ◽  
Image Processing Algorithm ◽  
Dual Purpose ◽  
Growth State ◽  
Good Ability ◽  
Set Up

The key to the design of the ground air dual-purpose agricultural information acquisition robot is the application of machine vision technology to realize the collection of crop growth state information. This research mainly designs the machine vision system of the ground air dual-purpose agricultural information acquisition robot, including hardware, software and image processing algorithm. The machine vision system designed in this paper can effectively complete the collection of crop status information. In order to verify the effectiveness of machine vision system, blueberry was used as the experimental object. The control group was set up indoor and outdoor, the fruit condition and quality information were detected, and the blueberry yield was estimated according to the test results. The experimental results show that the image segmentation algorithm in the vision system can identify blueberry fruit well, and the system has strong information analysis ability, and can accurately predict the quality and yield of blueberry fruit according to the image. It can be seen that the machine vision system has a good ability of information acquisition and recognition, which has a high reference significance for the design and research of the ground air dual-purpose agricultural information acquisition robot.

Multifunctional stereoscopic machine vision system with multiple 3D outputs

2020 ◽  
Keyword(s):  
Machine Vision ◽  
International Symposium ◽  
Fast Track ◽  
Vision System ◽  
Machine Vision System ◽  
Stereoscopic Displays ◽  
Electronic Imaging

Fast track article for IS&T International Symposium on Electronic Imaging 2020: Stereoscopic Displays and Applications proceedings.

scholarly journals A real-time machine-vision system for monitoring the textile raising process

2005 ◽  
Vol 56 (8-9) ◽  
pp. 831-842 ◽  
Author(s):  
Monica Carfagni ◽  
Rocco Furferi ◽  
Lapo Governi
Keyword(s):  
Machine Vision ◽  
Real Time ◽  
Vision System ◽  
Machine Vision System ◽  
Time Machine

Application of Machine Vision System in the Precision Inspection

2012 ◽  
Vol 546-547 ◽  
pp. 1382-1386
Author(s):  
Yin Xia Liu ◽  
Ping Zhou
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Machine Vision System ◽  
Technical Problems ◽  
Application Program ◽  
Precision Inspection ◽  
Machine Parts

In order to promote the application and development of machine vision, The paper introduces the components of a machine vision system、common lighting technique and machine vision process. And the key technical problems are also briefly discussed in the application. A reference idea for application program of testing the quality of the machine parts is offered.

A machine vision system for on-line removal of contaminants in wool

Mechatronics ◽  
2006 ◽  
Vol 16 (5) ◽  
pp. 243-247 ◽  
Author(s):  
Zhenwei Su ◽  
Gui Yun Tian ◽  
Chunhua Gao
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Machine Vision System ◽  
On Line ◽  
Removal Of Contaminants

A novel method based on machine vision system and deep learning to detect fraud in turmeric powder

2021 ◽  
pp. 104728
Author(s):  
Ahmad Jahanbakhshi ◽  
Yousef Abbaspour-Gilandeh ◽  
Kobra Heidarbeigi ◽  
Mohammad Momeny
Keyword(s):  
Deep Learning ◽  
Machine Vision ◽  
Vision System ◽  
Machine Vision System ◽  
Novel Method

Research on Machine Vision in Forestry Pluck System

2010 ◽  
Vol 139-141 ◽  
pp. 2199-2202
Author(s):  
Xin Li ◽  
Chun Liang Zhang ◽  
Li Jun Li ◽  
Zhi Hu
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Area Ratio ◽  
Self Organization ◽  
Machine Vision System ◽  
Camellia Oleifera ◽  
Threshold Method ◽  
Input Feature ◽  
Ga Algorithm ◽  
Forestry Industry

Forestry industry is an important part of nation's economy. In this paper, a machine vision system is presented as a key module of Camellia oleifera pluck robot. In order to cut fruit image up from complicate background, SOFM neural network and gray thresh is used in image segmentation. In SOFM method, take R-B,G-R,G-B and hue H tunnel as input feature vectors, use self-organization network to clustering can get the best effect. in gray threshold method can take various of method to get the best threshold, such as PSO and GA algorithm, and MATLAB includes the toolboxes. At last use noise ratio, area ratio, divided time, Fourier boundary descriptors and other indicators to assess the accuracy of segmentation. The methods have the significance to the current and subsequent research of forestry pluck device.

Sign in / Sign up

Export Citation Format

Share Document