scholarly journals Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform

2013 ◽  
Vol 15 (1) ◽  
pp. 80-94 ◽  
Author(s):  
S. Cubero ◽  
N. Aleixos ◽  
F. Albert ◽  
A. Torregrosa ◽  
C. Ortiz ◽  
...  
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Citrus Fruit ◽  
Mobile Platform ◽  
Computer Vision System

scholarly journals Neuronet search of special points for computer vision system when determining mobile platform movements

2014 ◽  
Author(s):  
М.О. Корлякова ◽  
◽  
Е.Ю. Прокопов ◽  
П.К. Новиков ◽  
◽  
...  
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Mobile Platform ◽  
Computer Vision System ◽  
Special Points

Identification of Citrus Fruit Defect using Computer Vision System

2021 ◽  
Author(s):  
Akshatha Prabhu ◽  
Likhitha S ◽  
Sangeetha K. V
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Citrus Fruit ◽  
Computer Vision System

scholarly journals In-Line Estimation of the Standard Colour Index of Citrus Fruits Using a Computer Vision System Developed For a Mobile Platform

2012 ◽  
Vol 6 (12) ◽  
pp. 3412-3419 ◽  
Author(s):  
A. Vidal ◽  
P. Talens ◽  
J. M. Prats-Montalbán ◽  
S. Cubero ◽  
F. Albert ◽  
...  
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Colour Index ◽  
Mobile Platform ◽  
Citrus Fruits ◽  
Computer Vision System

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

Colour assessment of milk and milk products using computer vision system and colorimeter

2021 ◽  
pp. 105084
Author(s):  
Bojana Milovanovic ◽  
Ilija Djekic ◽  
Jelena Miocinovic ◽  
Bartosz G. Solowiej ◽  
Jose M. Lorenzo ◽  
...  
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Computer Vision System ◽  
Milk Products

scholarly journals An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 343
Author(s):  
Kim Bjerge ◽  
Jakob Bonde Nielsen ◽  
Martin Videbæk Sepstrup ◽  
Flemming Helsing-Nielsen ◽  
Toke Thomas Høye
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Vision System ◽  
Low Cost ◽  
Light Trap ◽  
Automatic Monitoring ◽  
Light Sources ◽  
Monitoring Methods ◽  
Computer Vision System ◽  
Substantial Investment

Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.

scholarly journals Task Planner for Robotic Disassembly of Electric Vehicle Battery Pack

Metals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 387
Author(s):  
Martin Choux ◽  
Eduard Marti Bigorra ◽  
Ilya Tyapin
Keyword(s):  
Computer Vision ◽  
Electric Vehicles ◽  
Measurement Errors ◽  
Vision System ◽  
Lithium Ion ◽  
Battery Pack ◽  
Computer Vision System ◽  
Electric Vehicle Battery ◽  
Robotic Disassembly ◽  
Total Average

The rapidly growing deployment of Electric Vehicles (EV) put strong demands on the development of Lithium-Ion Batteries (LIBs) but also into its dismantling process, a necessary step for circular economy. The aim of this study is therefore to develop an autonomous task planner for the dismantling of EV Lithium-Ion Battery pack to a module level through the design and implementation of a computer vision system. This research contributes to moving closer towards fully automated EV battery robotic dismantling, an inevitable step for a sustainable world transition to an electric economy. For the proposed task planner the main functions consist in identifying LIB components and their locations, in creating a feasible dismantling plan, and lastly in moving the robot to the detected dismantling positions. Results show that the proposed method has measurement errors lower than 5 mm. In addition, the system is able to perform all the steps in the order and with a total average time of 34 s. The computer vision, robotics and battery disassembly have been successfully unified, resulting in a designed and tested task planner well suited for product with large variations and uncertainties.

Real-time Wearable Computer Vision System for Improved Museum Experience

2016 ◽  
Author(s):  
Giovanni Taverriti ◽  
Stefano Lombini ◽  
Lorenzo Seidenari ◽  
Marco Bertini ◽  
Alberto Del Bimbo
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Vision System ◽  
Wearable Computer ◽  
Computer Vision System ◽  
Museum Experience

scholarly journals Evaluating the diameter of eyedropper tips using a computer vision system

2019 ◽  
Vol 82 (1) ◽  
Author(s):  
Edicley Vander Machado ◽  
Priscila Cardoso Cristovam ◽  
Denise de Freitas ◽  
José Álvaro Pereira Gomes ◽  
Vagner Rogério dos Santos
Keyword(s):  
Computer Vision ◽  
Vision System ◽  
Computer Vision System
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