scholarly journals The grades and freshness assessment of eggs based on density detection using machine vision and weighing sensor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Supakorn Harnsoongnoen ◽  
Nuananong Jaroensuk
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Measuring System ◽  
Coefficient Of Determination ◽  
Water Displacement ◽  
Non Invasive ◽  
Future Potential ◽  
Non Destructive ◽  
Egg Freshness

AbstractThe water displacement and flotation are two of the most accurate and rapid methods for grading and assessing freshness of agricultural products based on density determination. However, these techniques are still not suitable for use in agricultural inspections of products such as eggs that absorb water which can be considered intrusive or destructive and can affect the result of measurements. Here we present a novel proposal for a method of non-destructive, non-invasive, low cost, simple and real—time monitoring of the grading and freshness assessment of eggs based on density detection using machine vision and a weighing sensor. This is the first proposal that divides egg freshness into intervals through density measurements. The machine vision system was developed for the measurement of external physical characteristics (length and breadth) of eggs for evaluating their volume. The weighing system was developed for the measurement of the weight of the egg. Egg weight and volume were used to calculate density for grading and egg freshness assessment. The proposed system could measure the weight, volume and density with an accuracy of 99.88%, 98.26% and 99.02%, respectively. The results showed that the weight and freshness of eggs stored at room temperature decreased with storage time. The relationship between density and percentage of freshness was linear for the all sizes of eggs, the coefficient of determination (R2) of 0.9982, 0.9999, 0.9996, 0.9996 and 0.9994 for classified egg size classified 0, 1, 2, 3 and 4, respectively. This study shows that egg freshness can be determined through density without using water to test for water displacement or egg flotation which has future potential as a measuring system important for the poultry industry.

Development of Machine Vision Positioning System of Magnetorheological Fluid (MRF) Actuator

2013 ◽  
Vol 470 ◽  
pp. 625-629
Author(s):  
A.B. Husaini ◽  
Ghazali Izzat ◽  
Samad Zahurin ◽  
Othman Rusli
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Feedback System ◽  
Magnetorheological Fluid ◽  
Fast Response ◽  
Positioning System ◽  
Machine Vision System ◽  
Vision Positioning ◽  
Magnetorheological Valve

Magnetorheological valve offers several advantages such as controllability, small in size and no moving part during operation. Thus, many researchers are working on developing an actuator based on this valve. However, this actuator required feedback system to improve it precision. This research is focusing on developing of machine vision based positioning system for MRF actuator. Image processing algorithms coded using Matlab software and directly connect to MRF valve controller. As a result, the system shows a fast response with processing time only 0.6 millisecond, system resolution is 0.1 millimeter and finally repeatability is 0.01. As a conclusion, the machine vision system are applicable for MRF actuator positioning system. This study is significant in order to developing a low cost and robust positioning system.

scholarly journals Machine Vision System Measuring the Trajectory of Upper Limb Motion Applying the Matlab Software

2019 ◽  
Vol 19 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Piotr Kuryło ◽  
Elena Pivarčiová ◽  
Joanna Cyganiuk ◽  
Peter Frankovský
Keyword(s):  
Machine Vision ◽  
Upper Limb ◽  
Vision System ◽  
Electronic Records ◽  
Application System ◽  
Non Invasive ◽  
Invasive Method ◽  
Full Analysis ◽  
Method Of Measurement ◽  
Rehabilitation Exercises

Abstract This paper discusses the problem of possibilities for applying a machine vision in the measurement of the trajectory of the upper limb movement in rehabilitation exercises. The fundamental presumption of designed system was to get the image from the camera’s CCD processor, possibilities of measuring and its processing. As a result of the application system, it is possible to dynamically determine the radius between the shoulder and forearm, and also the angle between the shoulder and the chest of the man, as function of the limb motion. The created system gives the possibility to use a non-invasive method of measurement, allows visualization and full analysis of the rehabilitation progress and also allows keeping electronic records of patients.

scholarly journals Liquid Level Detection in Standard Capacity Measures with Machine Vision

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2676
Author(s):  
Gregor Bobovnik ◽  
Tim Mušič ◽  
Jože Kutin
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Liquid Level ◽  
Measuring System ◽  
Legal Metrology ◽  
System A ◽  
Measurement Results ◽  
Capacity Measure ◽  
Measuring Scale ◽  
Liquid Level Detection

Capacity measures are commonly used volume standards for testing measuring systems for liquids other than water. Manual readings from the measuring scale can often be difficult due to the location of the capacity measure or to the nature of the measured liquid. This article focuses on the automation of this procedure by using a single camera machine vision system. A camera positioned perpendicular to the transparent neck captures the image of the liquid meniscus and the measuring scale. The volume reading is determined with the user-defined software in the LabVIEW programming environment, which carries out the image preprocessing, detection of the scale marks and the liquid level, correction of lens distortion and parallax effects and final unit conversions. The realized measuring system for liquid level detection in standard capacity measures is tested and validated by comparing the automated measurement results with those taken by the operators. The results confirm the appropriateness of the presented measuring system for the field of legal metrology.

scholarly journals Non-Invasive Estimation of Machining Parameters during End-Milling Operations Based on Acoustic Emission

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5326
Author(s):  
Andrés Sio-Sever ◽  
Erardo Leal-Muñoz ◽  
Juan Manuel Lopez-Navarro ◽  
Ricardo Alzugaray-Franz ◽  
Antonio Vizan-Idoipe ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
End Milling ◽  
Low Cost ◽  
Milling Process ◽  
Machining Process ◽  
Measuring System ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Processes ◽  
Non Invasive

This work presents a non-invasive and low-cost alternative to traditional methods for measuring the performance of machining processes directly on existing machine tools. A prototype measuring system has been developed based on non-contact microphones, a custom designed signal conditioning board and signal processing techniques that take advantage of the underlying physics of the machining process. Experiments have been conducted to estimate the depth of cut during end-milling process by means of the measurement of the acoustic emission energy generated during operation. Moreover, the predicted values have been compared with well established methods based on cutting forces measured by dynamometers.

Primary Study on Crop Wet Biomass Measuring with Dielectric Spectroscopy

2012 ◽  
Vol 443-444 ◽  
pp. 277-281
Author(s):  
Hua Zhang ◽  
Bai Yu Wu ◽  
Rui Feng Hou ◽  
Da Zhou Zhu ◽  
Da Yu Pan ◽  
...  
Keyword(s):  
Dielectric Spectroscopy ◽  
Plant Biomass ◽  
Measuring System ◽  
Coefficient Of Determination ◽  
Primary Study ◽  
Strongly Correlated ◽  
Element Analysis ◽  
Wet Biomass ◽  
Non Destructive

Crop wet biomass measuring with dielectric spectroscopy is a non-destructive method to quickly and accurately estimate plant biomass in situ. It optimizes the management of agronomists. An electrostatic free-space system was designed and tested to estimate crop wet biomass in situ. It acts as a parallel plate capacitor. The appropriate size of plate of the system is determined through Finite element analysis (FEA). Water is used to make the exclusion of interference at the earlier stage of the experiment, and Wheat is the experiment material. Results from the measuring system showed The Susceptance through the system was strongly correlated with wet biomass. The coefficient of determination (r2) is greater than 0.9.

scholarly journals A Robust Machine Vision Algorithm Development for Quality Parameters Extraction of Circular Biscuits and Cookies Digital Images

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Satyam Srivastava ◽  
Sachin Boyat ◽  
Shashikant Sadistap
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Monochromatic Light ◽  
Quality Parameters ◽  
Bakery Products ◽  
Robust Algorithms ◽  
Robust Algorithm ◽  
Detection And Identification ◽  
Specificity And Sensitivity

Biscuits and cookies are one of the major parts of Indian bakery products. The bake level of biscuits and cookies is of significant value to various bakery products as it determines the taste, texture, number of chocolate chips, uniformity in distribution of chocolate chips, and various features related to appearance of products. Six threshold methods (isodata, Otsu, minimum error, moment preserving, Fuzzy, manual method, and k-mean clustering) have been implemented for chocolate chips extraction from captured cookie image. Various other image processing operations such as entropy calculation, area calculation, parameter calculation, baked dough color, solidity, and fraction of top surface area have been implemented for commercial KrackJack biscuits and cookies. Proposed algorithm is able to detect and investigate about various defects such as crack and various spots. A simple and low cost machine vision system with improved version of robust algorithm for quality detection and identification is envisaged. Developed system and robust algorithm have a great application in various biscuit and cookies baking companies. Proposed system is composed of a monochromatic light source, and USB based 10.0 megapixel camera interfaced with ARM-9 processor for image acquisition. MATLAB version 5.2 has been used for development of robust algorithms and testing for various captured frames. Developed methods and procedures were tested on commercial biscuits resulting in the specificity and sensitivity of more than 94% and 82%, respectively. Since developed software package has been tested on commercial biscuits, it can be programmed to inspect other manufactured bakery products.

scholarly journals Ultrasonography as a predicting tool for carcass traits of young bulls

2003 ◽  
Vol 60 (4) ◽  
pp. 779-784 ◽  
Author(s):  
Liliane Suguisawa ◽  
Wilson Roberto Soares Mattos ◽  
Henrique Nunes de Oliveira ◽  
Antônio Carlos Silveira ◽  
Mário de Beni Arrigoni ◽  
...  
Keyword(s):  
Low Cost ◽  
Subcutaneous Fat ◽  
Carcass Composition ◽  
Frame Size ◽  
Non Invasive ◽  
Genetic Groups ◽  
Bull Calves ◽  
Subcutaneous Fat Thickness ◽  
Non Destructive ◽  
Support Research

Considerable resources have been allocated to support research in the development of non-invasive and non-destructive techniques for carcass composition and quality evaluation. Ultrasonography is a reliable and relatively low-cost technique that can be used. In the present study, real-time ultrasonography was used to predict ribeye area (REA) and subcutaneous fat thickness (FT) in live animals as compared to carcass measurements. Animals used were 115 yearling bull calves (initial body weight, 329 kg), kept under feedlot conditions, of four genetic groups (30, ½ Angus x Nellore; 30, ½ Canchim x Nellore; 30, ½ Simmental x Nellore, and 25 Nellore), and two finishing frame sizes (small and large). Four ultrasonographic measurements were taken every 28 days until slaughter. Predictive precision of ultrasonographic measurements increased as animals approached slaughter, reaching maximum values at the last measurement (R²=0.68 and 0.82 for REA and FT, respectively). FT carcass measurements was influenced by genetic group and live measurements (P < 0.05). Frame size did not influence REA and FT, probably due to small, but distinctive differences among genetic groups.

scholarly journals Implementation and potentials of a machine vision system in a series production using deep learning and low-cost hardware

Procedia CIRP ◽  
2020 ◽  
Vol 90 ◽  
pp. 611-616
Author(s):  
Hubert Würschinger ◽  
Matthias Mühlbauer ◽  
Michael Winter ◽  
Michael Engelbrecht ◽  
Nico Hanenkamp
Keyword(s):  
Deep Learning ◽  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Machine Vision System ◽  
Series Production

Machine Vision Analysis of Welding Region and its Application to Seam Tracking in Arc Welding

1993 ◽  
Vol 207 (4) ◽  
pp. 275-283 ◽  
Author(s):  
Y Li ◽  
J E Middle
Keyword(s):  
Machine Vision ◽  
Arc Welding ◽  
Vision System ◽  
Low Cost ◽  
Gas Metal Arc Welding ◽  
Seam Tracking ◽  
Optical Parameters ◽  
Robotic Welding ◽  
Radiated Energy ◽  
Welding Processes

Unlike the application of machine vision in many other fields, there is a particular problem in developing machine vision for automated and robotic welding processes, because the disturbance of the arc light deteriorates the field to be viewed. This paper describes an analysis of the radiated energy from the weld pool, and based on this describes how vision sensing of the welding region may be improved. An approach using specified pattern parameters is described to evaluate the ability to recognize an acquired image under different conditions such as with vidicons or sensor devices, different welding variables and optical parameters. Based on analysis of radiation from the welding region, a satisfactory wavelength range for sensing the image of the weld region is proposed and proved by experimentation. Images of gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW) regions have been modelled and successfully implemented for seam tracking control with a simultaneously developed low-cost vision system.

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