scholarly journals Machine Vision to Determine Agricultural Crop Maturity

10.5772/26213 ◽  
2012 ◽  
Author(s):  
Wan Ishak Wan Ismail ◽  
Mohd Hudzari
Keyword(s):  
Machine Vision ◽  
Agricultural Crop ◽  
Crop Maturity

scholarly journals Automated Date Fruits Sorting Machine using Fuzzy Logic Controller

2019 ◽  
Vol 8 (4) ◽  
pp. 1089-1093
Keyword(s):  
Fuzzy Logic ◽  
Machine Vision ◽  
Fuzzy Logic Controller ◽  
Animal Feed ◽  
Vision System ◽  
Vital Role ◽  
Human Consumption ◽  
Agricultural Crop ◽  
Ultrasonic Sensors ◽  
Date Fruits

Date palm is the primary agricultural crop in Oman. Date fruits occupy 80% of its share in total fruits production in Oman. Over 50% of agricultural lands are used to cultivate the date palms in Oman. Over 50% of its production is used for human consumption and others used for animal feed. In date fruits packaging industries, sorting system plays a vital role. So many techniques are adopted for this process. But, machine vision based system proved as efficient one. So, in this paper, the machine vision system is realized by color and ultrasonic sensors. The main aim of this work is to sort the date fruits based on its color, size and features. In this paper, the Fuzzy logic controller is used to sort the dates according to the signals from the color and ultrasonic sensors. The sorted fruits collected in separate trays with the help of servomotor which is actuated by neural network. The experimental results show that the proposed system is more precise and accurate in sorting the Date fruits.

Machine Vision

2009 ◽  
Author(s):  
Wesley E. Snyder ◽  
Hairong Qi
Keyword(s):  
Machine Vision

Classroom Lighting Energy-Saving Control System Based on Machine Vision Technology

2018 ◽  
pp. 143-149 ◽  
Author(s):  
Ruijie CHENG
Keyword(s):  
Control System ◽  
Machine Vision ◽  
Energy Saving ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Lighting Control ◽  
Lighting Energy ◽  
Neural Network Algorithm ◽  
Energy Saving Control ◽  
Model Algorithm

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.

Machine Vision, Let's Go into the Street

1997 ◽  
Vol 117 (10) ◽  
pp. 1339-1344
Author(s):  
Katsuhiko Sakaue ◽  
Hiroyasu Koshimizu
Keyword(s):  
Machine Vision

Machine Vision Technologies to Connect with Humans

2005 ◽  
Vol 125 (11) ◽  
pp. 692-695
Author(s):  
Kazunori UMEDA ◽  
Yoshimitsu AOKI
Keyword(s):  
Machine Vision

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.

A Flying Gray Ball Multi-illuminant Image Dataset for Color Research

2020 ◽  
Vol 64 (5) ◽  
pp. 50411-1-50411-8
Author(s):  
Hoda Aghaei ◽  
Brian Funt
Keyword(s):  
Machine Vision ◽  
Spectral Reflectance ◽  
Color Constancy ◽  
Ground Truth ◽  
Practical Approach ◽  
Post Processing ◽  
Illumination Estimation ◽  
Processing Step ◽  
Image Dataset

Abstract For research in the field of illumination estimation and color constancy, there is a need for ground-truth measurement of the illumination color at many locations within multi-illuminant scenes. A practical approach to obtaining such ground-truth illumination data is presented here. The proposed method involves using a drone to carry a gray ball of known percent surface spectral reflectance throughout a scene while photographing it frequently during the flight using a calibrated camera. The captured images are then post-processed. In the post-processing step, machine vision techniques are used to detect the gray ball within each frame. The camera RGB of light reflected from the gray ball provides a measure of the illumination color at that location. In total, the dataset contains 30 scenes with 100 illumination measurements on average per scene. The dataset is available for download free of charge.

Application of Remote Sensing in Agriculture

2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Jan Piekarczyk
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Crop Production ◽  
Satellite Images ◽  
Crop Yields ◽  
Spatial Scales ◽  
Strong Relationship ◽  
Physical Parameters ◽  
Agricultural Crop ◽  
Remote Sensing Methods

AbstractWith increasing intensity of agricultural crop production increases the need to obtain information about environmental conditions in which this production takes place. Remote sensing methods, including satellite images, airborne photographs and ground-based spectral measurements can greatly simplify the monitoring of crop development and decision-making to optimize inputs on agricultural production and reduce its harmful effects on the environment. One of the earliest uses of remote sensing in agriculture is crop identification and their acreage estimation. Satellite data acquired for this purpose are necessary to ensure food security and the proper functioning of agricultural markets at national and global scales. Due to strong relationship between plant bio-physical parameters and the amount of electromagnetic radiation reflected (in certain ranges of the spectrum) from plants and then registered by sensors it is possible to predict crop yields. Other applications of remote sensing are intensively developed in the framework of so-called precision agriculture, in small spatial scales including individual fields. Data from ground-based measurements as well as from airborne or satellite images are used to develop yield and soil maps which can be used to determine the doses of irrigation and fertilization and to take decisions on the use of pesticides.

ORGANOPHOSPHORUS NEUROTOXINS

2020 ◽  
Author(s):  
Mariya Andriyanova ◽  
Aslanli Aslanli ◽  
Nataliya Basova ◽  
Viktor Bykov ◽  
Sergey Varfolomeev ◽  
...  
Keyword(s):  
Crop Protection ◽  
Chemical Warfare Agents ◽  
Agricultural Crop ◽  
Current State ◽  
Physicochemical Biology ◽  
Chemical Agents ◽  
Warfare Agents ◽  
History Of ◽  
Physicochemical Methods ◽  
State Of Research

The collective monograph is devoted to discussing the history of creation, studying the properties, neutralizing and using organophosphorus neurotoxins, which include chemical warfare agents, agricultural crop protection chemical agents (herbicides and insecticides) and medicines. The monograph summarizes the results of current scientific research and new prospects for the development of this field of knowledge in the 21st century, including the use of modern physicochemical methods for experimental study and theoretical analysis of biocatalysis and its mechanisms based on molecular modeling with supercomputer power. The book is intended for specialists who are interested in the current state of research in the field of organophosphorus neurotoxins. The monograph will be useful for students, graduate students, researchers specializing in the field of physical chemistry, physicochemical biology, chemical enzymology, toxicology, biochemistry, molecular biology and genetics, biotechnology, nanotechnology and biomedicine.

Effect of Field Setup on Accuracy of Traffic Data Collection Using Machine Vision Technology

2002 ◽  
Vol 1804 (1) ◽  
pp. 62-66 ◽  
Author(s):  
Sunita Nadella ◽  
Lloyd A. Herman
Keyword(s):  
Machine Vision ◽  
Focal Length ◽  
Reference Points ◽  
Specific Reference ◽  
Traffic Data ◽  
Video Traffic ◽  
Vertical Angle ◽  
Traffic Data Collection ◽  
Camera Position ◽  
Parameter Ranges

Video traffic data were collected in 24 combinations of four different camera position parameters. A machine vision processor was used to detect vehicle speeds and volumes from the videotapes. The machine vision results were then compared with the actual vehicle volumes and speeds to give the percentage errors in each case. The results of the study provide a procedure with which to establish camera position parameters with specific reference points to help machine vision users select suitable camera positions and develop appropriate measurement error expectations. The camera position parameters that were most likely to produce the least overall volume and speed errors, for the specific site and field setup with the parameter ranges used in this study, were the low height of approximately 7.6 m (25 ft), with an upstream orientation (traffic moving toward the camera), a 50-mm (midangle) focal length, and a 15° vertical angle.

Sign in / Sign up

Export Citation Format

Share Document