scholarly journals THE APPLICATION OF COMPUTER VISION FOR THE ESTIMATION OF SHRINKAGE AND DEFORMATION OF THIN MANGO SLICES DURING AIR DRYING PROCESS

2021 ◽  
Vol 11 (4) ◽  
pp. 44-55
Author(s):  
Nguyen Duc Trung ◽  
Pham Thanh Huong ◽  
Nguyen Ngoc Hoang ◽  
Dang Minh Hieu ◽  
Nguyen Nang Chat ◽  
...  
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Control Process ◽  
Digital Camera ◽  
Convective Drying ◽  
Drying Process ◽  
Size And Shape ◽  
Quality Control Process ◽  
Drying Conditions ◽  
Human Eyes

Computer vision has been currently a new trend in developing new tools for automatic real-time quality control process in food drying. During drying process, the size and shape of mango slides are critically changed. These changes usually determine the sensorial value of products, as well as which drying conditions would be needed to obtain the highest quality of dried products. In this study, we report on the development of a computer vision tool, requiring a normal digital camera installed, to evaluate the changes in size and shape of mango slides during the drying process. The technique is expected to replace the observation with human eyes to evaluate the changes of food products during the drying process, which might not be able to provide reliable and consistent judgements all the time. Image of drying mango slide is taken by a digital camera, then the feature extraction is implemented. The area of mango slice is determined by the area ratio via the pixel number counting and the comparison to an original sample with predefined reference size. The shrinkage deformation is evaluated by elliptical fitting to develop the automated utility. The utility is built on MATLAB platform. The variations in size and shape of the mango slices during a convective drying process with different processing conditions are examined and acquired by the built software which achieves real-time performance on the personal laptop.

Computer vision technology for real-time food quality assurance during drying process

2014 ◽  
Vol 39 (1) ◽  
pp. 76-84 ◽  
Author(s):  
Mortaza Aghbashlo ◽  
Soleiman Hosseinpour ◽  
Mahdi Ghasemi-Varnamkhasti
Keyword(s):  
Computer Vision ◽  
Quality Assurance ◽  
Real Time ◽  
Food Quality ◽  
Drying Process ◽  
Computer Vision Technology

scholarly journals Deep learning for the quality control of thermoforming food packages

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Núria Banús ◽  
Imma Boada ◽  
Pau Xiberta ◽  
Pol Toldrà ◽  
Narcís Bustins
Keyword(s):  
Computer Vision ◽  
Quality Control ◽  
Deep Learning ◽  
Production Line ◽  
Modular Design ◽  
Vision System ◽  
False Negative ◽  
Control Process ◽  
Food Packages ◽  
Quality Control Process

AbstractQuality control is a key process designed to ensure that only products satisfying the defined quality requirements reach the end consumer or the next step in a production line. In the food industry, in the packaging step, there are many products that are still evaluated by human operators. To automate the process and improve efficiency and effectiveness, computer vision and artificial intelligence techniques can be applied. This automation is challenging since specific strategies designed according to the application scenario are required. Focusing on the quality control of the sealing and closure of matrix-shaped thermoforming food packages, the aim of the article is to propose a deep-learning-based solution designed to automatically perform the quality control while satisfying production cadence and ensuring 100% inline inspection of the products. Particularly, the designed computer vision system and the image-based criteria defined to determine when a product has to be accepted or rejected are presented. In addition, the vision control software is described with special emphasis on the different convolutional neural network (CNN) architectures that have been considered (ResNet18, ResNet50, Vgg19 and DenseNet161, non-pre-trained and pre-trained on ImageNet) and on the specifically designed dataset. To test the solution, different experiments are carried out in the laboratory and also in a real scenario, concluding that the proposed CNN-based approach improves the efficiency and security of the quality control process. Optimal results are obtained with the pre-trained DenseNet161, achieving false positive rates that range from 0.03 to 0.30% and false negative rates that range from 0 to 0.07%, with a rejection rate between 0.64 and 5.09% of production, and being able to detect at least 99.93% of the sealing defects that occur in any production. The modular design of our solution as well as the provided description allow it to adapt to similar scenarios and to new deep-learning models to prevent the arrival of faulty products to end consumers by removing them from the automated production line.

scholarly journals Influence of the low temperature drying process on optical alternations of organic apple slices

2018 ◽  
Author(s):  
Christian Andre Kopp ◽  
M. Bantle ◽  
I.C. Claussen ◽  
I. Tolstorebrov
Keyword(s):  
Product Quality ◽  
Color Space ◽  
Optical Parameter ◽  
Convective Drying ◽  
Sensor Technology ◽  
Drying Process ◽  
Camera System ◽  
Apple Slices ◽  
Drying Conditions ◽  
Conventional Systems

Drying conditions for convective driers are often based on empirical approaches in which the final product quality is evaluated post processing. Modern sensor technology and data processing enable second-by-second quality analyses but conventional systems do not utilize this possibility. An industrial convective drying chamber was modified with a camera system to investigate the product during the drying process. The obtained data was analyzed on color alternation (CIE-L*a*b* color space and Browning Index), shrinkage and deformation. Both, shrinkage and deformation show minor dependence on drying conditons. The investigation shows the time depending optical parameter at different drying conditions. This might offer new "smart" drying programs with focus on improved product quality. Keywords: color alternation; shrinkage; deformation; convective drying; smart drying

Acoustic Auditing as a Real-Time, Non-invasive Quality Control Process for Both Source and Assay Plates

2005 ◽  
Vol 3 (4) ◽  
pp. 425-437 ◽  
Author(s):  
Joseph Olechno ◽  
Richard Ellson ◽  
Brent Browning ◽  
Richard Stearns ◽  
Mitchell Mutz ◽  
...  
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Control Process ◽  
Non Invasive ◽  
Quality Control Process

Video real-time imaging of artificial membranes during freeze-drying by cryo-electron microscopy

1988 ◽  
Vol 46 ◽  
pp. 16-17
Author(s):  
Alan S. Rudolph ◽  
Ronald R. Price
Keyword(s):  
Real Time ◽  
Self Assembly ◽  
Freeze Drying ◽  
Video Capture ◽  
Drying Process ◽  
Artificial Membranes ◽  
The Past ◽  
Cryo Electron Microscopy ◽  
Spherical Structures ◽  
Capture Techniques

We have employed cryoelectron microscopy to visualize events that occur during the freeze-drying of artificial membranes by employing real time video capture techniques. Artificial membranes or liposomes which are spherical structures within internal aqueous space are stabilized by water which provides the driving force for spontaneous self-assembly of these structures. Previous assays of damage to these structures which are induced by freeze drying reveal that the two principal deleterious events that occur are 1) fusion of liposomes and 2) leakage of contents trapped within the liposome [1]. In the past the only way to access these events was to examine the liposomes following the dehydration event. This technique allows the event to be monitored in real time as the liposomes destabilize and as water is sublimed at cryo temperatures in the vacuum of the microscope. The method by which liposomes are compromised by freeze-drying are largely unknown. This technique has shown that cryo-protectants such as glycerol and carbohydrates are able to maintain liposomal structure throughout the drying process.

Analysis of the information management system in the manufacturing process of cigarette enterprises using fuzzy AHP

2021 ◽  
pp. 1-11
Author(s):  
Song Gang ◽  
Wang Xiaoming ◽  
Wu Junfeng ◽  
Li Shufang ◽  
Liu Zhuowen ◽  
...  
Keyword(s):  
Quality Control ◽  
Production Process ◽  
Information Management ◽  
Manufacturing Process ◽  
Management System ◽  
Fuzzy Ahp ◽  
Control Process ◽  
Information Management System ◽  
Manufacturing Execution System ◽  
Quality Control Process

In view of the production quality management of filter rods in the manufacturing and execution process of cigarette enterprises, this paper analyzes the necessity of implementing the manufacturing execution system (MES) in the production process of filter rods. In this paper, the filter rod quality system of cigarette enterprise based on MES is fully studied, and the constructive information management system demand analysis, cigarette quality control process, system function module design, implementation and test effect are given. This paper utilizes the Fuzzy analytic hierarchy process to find the optimal system for processing the manufacturing of cigarette. The implementation of MSE based filter rod quality information management system for a cigarette enterprise ensures the quality control in the cigarette production process. Through visualization, real-time and dynamic way, the information management of cigarette production is completed, which greatly improves the quality of cigarette enterprise manufacturing process.

Mitocytosis, a migrasome-mediated mitochondrial quality-control process

Cell ◽  
2021 ◽  
Vol 184 (11) ◽  
pp. 2896-2910.e13
Author(s):  
Haifeng Jiao ◽  
Dong Jiang ◽  
Xiaoyu Hu ◽  
Wanqing Du ◽  
Liangliang Ji ◽  
...  
Keyword(s):  
Quality Control ◽  
Control Process ◽  
Mitochondrial Quality Control ◽  
Quality Control Process
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