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Machine Vision systems combine image processing with industrial automation. One of the primary areas of application of Machine Vision in the Industry is in the area of Quality Control. Machine vision provides fast, economic and reliable inspection that improves quality as well as business productivity. Building machine vision applications is a chal...
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In modern manufacturing, the detection and prediction of machine anomalies, i.e., the inactive state of the machine during operation, is an important issue. Accurate inactive state detection models for factory machines can result in increased productivity. Moreover, they can guide engineers in implementing appropriate maintenance actions, which can...
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... The use of 3D-vision measurement methods and imaging is present in many areas of industrial production [13]. These types of non-contact measuring systems are used in the processing of plastics, wood, metals, or composite materials [14,15]. ...
An effective chip formation process is significant for an efficient metal-cutting process. Long continuous chips can lead to scratches on the machined surface, increasing the risk to operator safety and stability of the machining process. The use of chip grooves on cutting inserts allows for control of the chip formation and breaking process during machining. The shape of the rake surface and the design of the chip groove also affect the efficiency of the machining process. The article presents the use of 3D imaging to analyze changes in the selected chip groove shapes depending on the cutting depth ap = 0.10, 0.25, and 0.50 mm and the angular location of the cutting insert relative to the machined surface of the workpiece (i.e., major cutting-edge angle K = 60° and K = 90°). The analysis methodology was based on the use of 3D image registration and surface shape modeling. In the analysis based on the 3D imaging presented, the novelty was the adaptation of methods typically used to map and model the terrain surface, which have not been used previously in cutting processes. The evaluation of the shape of the chip groove surface was carried out using, e.g., watershed maps and 3D surface maps. The obtained results indicated a significant influence of the cutting depth and major cutting-edge angle on the surface shape, profile, and length of the chip former; chip groove volume; and the theoretical contact area of the formed chip with the cutting insert. It was observed that for small depths of cut, i.e., ap < 0.25 mm, the chip-curling process may be difficult due to the flattened shape of the rake surface. In addition, the influence of the convexity of the rake surface of the cutting insert on the chip formation process was demonstrated. The results of the experimental research that verified the conclusions are presented. The developed results may be useful in the process of selecting the parameters and conditions of the metal finishing through use of tools with a shaped rake surface.
... The most common type of transformation used for this kind of image is the 2D affine. This geometric transformation is a linear mapping method that preserves the points, straight lines and planes, but not angles and length (even though ratios) [40]. For instance, with this transformation, a rectangle becomes a parallelogram. ...
Full spherical views provide advantages in many applications that use visual information. Dual back-to-back fisheye cameras are receiving much attention to obtain this type of view. However, obtaining a high-quality full spherical view is very challenging. In this paper, we propose a correction step that models the relation between the pixels of the pair of fisheye images in polar coordinates. This correction is implemented during the mapping from the unit sphere to the fisheye image using the equidistant fisheye projection. The objective is that the projections of the same point in the pair of images have the same position on the unit sphere after the correction. In this way, they will also have the same position on the equirectangular coordinate system. Consequently, the discontinuity between the spherical views for blending is minimized. Throughout the manuscript, we show that the angular polar coordinates of the same scene point in the fisheye images are related by a sine function and the radial distance coordinates by a linear function. Also, we propose employing a polynomial as a geometric transformation between the pair of spherical views during the image alignment since the relationship between the matching points of pairs of spherical views is not linear, especially in the top/bottom regions. Quantitative evaluations demonstrate that using the correction step improves the quality of the full spherical view, i.e. IQ MS-SSIM, up to 7%. Similarly, using a polynomial improves the IQ MS-SSIM up to 6.29% with respect to using an affine matrix.
... To facilitate block chain transactions, various third-birthday birthday celebration corporations might also be noncommissioned. Some examples contain value processors, clever contracts and block chain value platforms [22,23,25]. These third-birthday birthday celebration blockchain corporations often have comparatively prone protection on their terribly own apps and websites, which could conjointly in addition escape the door hospitable hacking. ...
Blockchain technology may be a recent advancement and offers a ground-breaking technique for keeping the knowledge for an extended time and completing transactions like knowledge management, knowledge handling, performing arts functions, associated establishing trust in an open atmosphere. Most of them are considering block chain as a technology innovation significantly for cryptography and cyber security with systems like bitcoin, IoT, sensible Grids and etc., albeit this technology proofs its name and has received ton and ton of growing interests in multiple dimensions, the safety and security of the block chains are still in analysis whereas deploying block chain in versatile domains and environments. This work elaborates a comprehensive summary of the safety and privacy of block chain from knowledge management perspective. attention platform is employed for implementation and testing. Around 20,000 records are being taken and valid mistreatment the projected algorithmic program. Initially, a block chain is created using distributed information, which tracks an ever-changing list of trading records by organising them into a hierarchic chain of block. Because attention knowledge necessitates greater security, a peer-to-peer overlay network is used to create and maintain the block chain, which is secured through the intelligent and suburbanized use of cryptography with crowd computing. ALM algorithmic program projected has been increased with applicable knowledge possession by providing 2 issue authentications with an accuracy of 95%.The projected system may be a decentralized system and thence guaranteeing higher knowledge transparency and auditability. Security and privacy properties are being ensured by providing fine grained access management on the highest of the ALM encoding. Hence, Security and privacy problems with current scenario are addressed well with a high-level access management rulesets.
... Computer vision technology collects high-quality images by CCD camera, then constructs models by analyzing accurate mathematical statistics to achieve high-precision measurement. There are many software modules, such as linear regression, learning vector method, neural networks, and other algorithms, which are included in the image digitization module, digital image processing module, intelligent judgment decision-making module, and others [33]. In this section, we will introduce a variety of imaging methods of machine vision technology (RGB imaging, multispectral imaging, hyperspectral imaging, Raman imaging, and THz imaging) that can be used to analyze tea color, shape, texture, and image features. ...
Tea is one of the world’s three most popular beverages, so the detection of its quality (physical, chemical, microbiological, and classified parameters), as well as its safety (inorganic and organic contaminants), is a very crucial process. Emerging technologies (spectral technology, computer vision, electronic nose, electronic tongue, and electrochemical methods) have provided a fast, nondestructive (or light damaging) and convenient method for the detection of tea products, including fresh, fermented, and processed tea leaves, and commercial tea. These technologies are beneficial for automating the tea processing process, improving the quality and production of tea, and increasing the economic benefits for the industry. Furthermore, it can also provide ideas regarding the detection and evaluation of other food products.
... Machine Vision Systems (MVS) involve cameras capturing images, which are then processed using vision software. The results are compared with predefined standards to determine the appropriate response, such as accepting or rejecting a manufactured part [10,5,8,11,9]. One of the significant challenges in computer vision is detecting occluded objects, especially when objects are grouped together. ...
Object detection is a classic research problem in the area of Computer Vision. Many smart world applications, like, video surveillance or autonomous navigation systems require a high accuracy in pose detection of objects. One of the main challenges in Object detection is the problem of detecting occluded objects and its respective 3D reconstruction. The focus of this paper is inter-object occlusion where two or more objects being tracked occlude each other. A novel algorithm has been proposed for handling object occlusion by using the technique of geometric matching and its 3D projection obtained. The developed algorithm has been tested using sample data and the results are presented.
... Quality inspections can be conducted at any stage of the industrial production circle, such as product components, products within the manufacturing lines, incoming material, or finished products. Inspection examines products to determine those that meet the set standards and those that deviate from the set quality requirements, paving the way for the rejection of faulty products and progression to the next stage of those that conform to the set standards [1]. In situ or in-process inspections are standard practices conducted during industrial parts and other product manufacturing processes [2]. ...
The need to overcome the challenges of visual inspections conducted by domain experts drives the recent surge in visual inspection research. Typical manual industrial data analysis and inspection for defects conducted by trained personnel are expensive, time-consuming, and characterized by mistakes. Thus, an efficient intelligent-driven model is needed to eliminate or minimize the challenges of defect identification and elimination in processes to the barest minimum. This paper presents a robust method for recognizing and classifying defects in industrial products using a deep-learning architectural ensemble approach integrated with a weighted sequence meta-learning unification framework. In the proposed method, a unique base model is constructed and fused together with other co-learning pretrained models using a sequence-driven meta-learning ensembler that aggregates the best features learned from the various contributing models for better and superior performance. During experimentation in the study, different publicly available industrial product datasets consisting of the defect and non-defect samples were used to train, validate, and test the introduced model, with remarkable results obtained that demonstrate the viability of the proposed method in tackling the challenges of the manual visual inspection approach.
... We utilized a machine learning method to enable the learning process. Machine learning is a powerful tool to conduct quality inspection [2] [7]. Our proposed solution can automatically find the product measurement and threshold values fed to the Odoo quality control module by using the baby biscuit production process in our experiment. ...
Odoo is one of the top Enterprise Resource Planning (ERP) applications. In particular, it is supported by a quality control module with the ability to control, trigger an alert, and check its purpose. This research strives to supplement the existing Odoo quality control module with parameters from past inspection data obtained before quality control migrates to Odoo. To support the study, we used a machine learning method to discover the intrinsic pattern from the dataset of quality control in the production process of baby biscuit products. The experiment shows that the additional quality control feature can provide the product measurement and tolerance threshold fed into Odoo quality control module. The additional feature is helpful for decision making and error minimization in setting quality control parameters and tolerance threshold. Furthermore, a high accuracy rate of 95.71% is obtained from the employed Decision Tree algorithm.
