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 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 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.

scholarly journals QUALITY INSPECTION OF BAKERY PRODUCTS USING A COLOR-BASED MACHINE VISION SYSTEM

2000 ◽  
Vol 23 (1) ◽  
pp. 39-50 ◽  
Author(s):  
MOHD ZAID ABDULLAH ◽  
SABINA ABDUL AZIZ ◽  
ABDUL MANAN MOHAMED
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Bakery Products ◽  
Quality Inspection ◽  
Machine Vision System
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