Determination of yarn production characteristics using image processing

The digital image acquisition and processing technology already mature also in domains and so on visual communication obtains day by day[1]. However, the image acquisition and processing technology had many kinds, for example white balance processing and image denoising methods. The traditional image acquisition and processing systems are implemented using software by the PC or DSP chip[2], and sometimes software in series can not meet the requirement of high speed image processing. this article has given FPGA in the image acquisition and processing simple application, applied FPGA in the image acquisition and processing to be possible to enhance the image processing the speed, reduced takes the logical unit. The system designed by above-mentioned way achieves a satisfying effect by experimental verification.

In this paper, a multi-input computer system for image acquisition and processing is presented. This system is equipped with a 2-wavelength thermal channel and any 4 other ones, which can be used to capture visual, X-ray, ultrasound images, etc. Novel image processing tools are described, mainly for geometrical and 3D transformations.

Currently, the fast evolution of cameras in recent years has made them promising tools for diagnostics of Tokamak. The solution presented in this paper consists of a prototype of high-speed visible image acquisition and processing system (HVIAPs) dedicated for experimental advanced superconducting tokamak shape and position control. Graphics processing unit (GPU) and field-programmable gate array (FPGA) are typically used as accelerators or co-processors in addition to a CPU. Such a heterogeneous computing system can combine the advantages of its individual components. The main imaging equipment components used for this system are four high-resolution fast cameras equipped with fiber interface. Image data from the cameras are received by the frame grabber card based on the FPGA and transmitted to the GPU via the peripheral component interconnect express interface. The software support for the system includes low-level drivers and application programming interface libraries for all components and the algorithm developed for image processing. The offline image process results are compared to equilibrium fitting code, which is a commonly used reconstruction method, with an average error of 1.5 cm. The total processing time for one frame is less than 0.3 ms.

A high-speed multi-channel multi time delay and integration charge couple device(TDICCD) image acquisition and processing system is introduced in this paper. FPGA is the core logic control of the system. The main hardware component of the system and the implementation method of FPGA are described and the diagrams of main modules are presented. Software workflow and a variety of image processing methods are also given. Test results show that the design achieves data transfer speed of 2.4Gbps and realizes real-time processing of image for high-speed multi-channel TDICCD camera so that meets the system requirement.

A three-dimensional (3D) laser scanning system is the main part of reverse engineering. It is a comprehensive technological system, including numerical control (NC), a laser, computer-aided design/manufacturing (CAD/CAM), precision mechanisms, computing image sampling, and image processing. Generally, it consists of a motion control system, an image sampling system, and an image processing system, etc. This paper focuses on introducing control principles, hardware constitutions, and software algorithms of the servo motion system, and analyzes and presents the hardware constitutions, software algorithms, and experimental results of the image sampling and processing system in great detail. Finally, the authors come to the conclusion that the errors all occur within the range ±0.1 mm.

VME image acquisition and processing using standard TV CCD cameras

In recent years, the post‐harvest commercialization of fresh jujube sorting technology is backward, the efficiency of manual grading is low, and the application of machine vision technology in fruit grading has been a research hotspot. To improve the grading accuracy and speed of the fresh jujube machine vision grading machine, this study designs a method of fresh jujube machine vision grading using an electromagnetic synchronous actuator. The grading machine consists of an automatic distribution and arrangement system, an image acquisition and processing system, and a synchronous actuator assembly, which uses a sensitive electromagnet to adsorb a silicon steel switching buckling plate to execute the action. The image processing process includes an image color component, Sobel operator filtering, Otsu method binarization, and ellipse fitting to extract the color and size eigenvalues. The experimental results show that the date images can be acquired quickly and processed accurately with a processing speed of 50 ms per frame. In addition, the proposed actuator can be sensitively triggered with a response time of 40 ms. The grader successfully classified jujube into five size classes and one color class. The grading accuracy and non‐destructive rate reached 93.7% and 100%, respectively. The grading efficiency is 20 jujubes per second, with a maximum production rate of 1400 kilograms per hour. This grading machine realizes the requirements of high accuracy, high speed, and non‐destructive grading of fresh jujube and provides an important technical and theoretical basis for the development of machine vision jujube rapid grading technology.Practical applicationsIn recent years, sorting technology in the post‐harvest commercialization of fruits has been outdated, and manual grading has been inefficient. The application of machine vision technology in fruit grading has been a research hotspot in recent years. This study designs a machine vision grading of fresh dates with an electromagnetic synchronous actuator. The grader was composed of a roller conveyor, synchronous actuator assembly, image main processor, and actuator controlling co‐processor. Experimental results indicated that jujube images could be acquired rapidly and processed accurately, with a processing speed of 50 ms per frame. In addition, the proposed actuator could be sensitively triggered with a response time of 40 ms. Finally, the grader successfully sorted jujubes into five size classes and one color class. The grading accuracy rate and non‐destructive rate reached 93.7% and 100%, respectively. The grading efficiency was 20 jujubes per second, and the maximum productivity was 1400 kg/h.

Skin moles and lesions can be the first signs of severe skin diseases such as cancer. This paper presents the development of an end-user device capable of capturing images, segmentation and diagnosis of moles by using the ABCD rule, which stands for analyzing moles’ parameters as: asymmetry, border, color, and diameter. These are the main mole characteristics that doctors look at, each of them having a different factor of importance, and depending on these an accurate diagnosis can be given. For the hardware, we developed a small and compact device that can be manipulated easily by anyone without knowledge of medicine, in which we considered a custom-designed 3D enclosure with two white LEDs to control the light. The device has the role of facilitating analysis of the suspicious moles regularly at home, even if only from an indicative and not from a medical point of view. The developed PC software permits the storage of the images in a local database for easy tracking and analysis in time. The image processing developed for the ABCD rule is incorporated into the PC software and tested extensively on the international PH2 database with skin melanoma images to validate our segmentation and criteria evaluation. Using the developed device, we captured mole images for patients, who also took a medical examination by a specialist using the standard dermatoscope. Therefore, we obtained our own database containing 26 images for which we have also the specialists’ diagnosis. The performance evaluation measures obtained using our device are—Accuracy: 0.92, Precision: 1.0, Recall: 0.92, F1-score: 0.96.

In the weld image acquisition system, real-time image processing has been a difficult design bottleneck to break through, especially for the occasion of large data processing capability and more demanding real-time requirements, in which the traditional MCU can not adapt, so using high-performance FPGA as the core of the high speed image acquisition and processing card, better meets the large amount of data in most of the image processing system and high demanding real-time requirements. At the same time, system data collection, storage and display were implemented by using Verilog, and in order to reducing the influence of edge detection noise, the combination of image enhancement and median filtering image preprocessing algorithm was used. Compared to the pre-processing algorithm of the software implementation, it has a great speed advantage, and simplifies the subsequent processing work load, improves the speed and efficiency of the entire image processing system greatly. So it proves that the system has strong ability of restraining the noise of image, and more accurate extracted edge positioning, it can be applied in the seam tracking field which need higher real-time requirements.

Video-based speckle interferometric methods such as electronic speckle pattern interferometry (ESPI) allow us to measure full-field surface deformation of a diffuse object. In this paper we show, in a first step, that the susceptibility of ESPI to noise can be substantially reduced [1] by synchronizing the optical interferometer and the object stressing system with the CCD image acquisition and processing system, and by performing what amounts to a repetitive sequence of rapid ESPI tests. In this manner, a stable fringe pattern can be obtained as long as the ambient noise is of sufficiently lower frequency than the video acquisition rate (typically 30 Hz). This scheme will be referred in this paper as reference-updating subtractive correlated ESPI to distinguish it from classical ESPI. We then take this issue further with a hybrid additive-subtractive decollated ESPI technique that will freeze out unwanted environmental noise of frequencies much higher than video rates [2], The basic principle of this proposed technique can be summed up as follows: (i) acquire speckle images containing information about the same two deformed object states in every frame of the image acquisition sequence, (ii) decorrelate the speckles between every frame, and (iii) compare every consecutive pair of speckle images to extract visible fringes corresponding to the two deformed states of the test object.

With increasing applications of image processing in manufacturing, it has become necessary to provide industry with powerful as well as flexible means of adapting the technology to the solution of different kinds of tasks at hand. Besides the standard components of an image processing system, the availability ofvarious software tools to fill the gap between design, digitization, measurement and the manufacturing phases should be emphasized. The users could e.g., desire to transfer grabbed images into certain computer graphics data format for further processing. They may want to apply image processing for the measurement of machine parts interactively or automatically, or they may want to convert the pictures processd, e.g. with edge detectors, into some CAD data format, or even to generate a numerical control file to machine the parts directly from the image processing data. With this motivation, two software packages FIPS—Flexible Image Processing System, and IQIS— Integrated QUality Inspection System have been developed for manufacturing and quality inspection and have been used by industry for various purposes from simple image digitization and processing, luminance adjustment, data and file format conversion, generation of control files for numerical control in laser cuffing, to direct control of robot movement, and interactive as well as automatic machine part measurement.

Demarcation of nonmelanoma skin cancer margins in thick excisions using multispectral polarized light imaging.

This paper presents an embedded platform for image acquisition and processing. It is based on the Texas Instruments' TMS320C6416T, a high performance digital signal processor and Altera's FPGA EP3C25F324, offering 594 Kbits embedded memory, which is enough to design a large FIFO (first in first out) on chip. The digital image data is transferred into FPGA, after pre-processing, it is transferred into DSP6416 by the interface of FIFO in FPGA and DSP6416 EMIF. Then the image data is processed in DSP by the real time algorithms. And this system provides the LVDS interface for displaying the real-time image and CAN interface for communication with other devices. Experiments results show that this system is useful and powerful.

The non-invasive system based on machine vision has been widely used in the field of surface defect detection for flat steel products. However, due to the steel features of multiple surfaces, various specifications and changeable producing speeds, on-line surface defect detection for the special-shaped steel products is still a great challenge. In view of the above problems, a non-invasive system, which is suitable for the on-line detection of special-shaped steel, is designed and introduced in this paper. Specifically, the proposed system is composed of two subsystems working in coordination: an image acquisition system and an image processing system. The image acquisition system, which adopts a specifically developed image acquisition device as the core, can obtain high-quality full-surface images of steel with different specifications. The image processing system can detect surface defects by embedding the latest YOLOv5 algorithm. The results show a satisfactory performance in both detection speed and precision, which confirm that the proposed system can be reliably employed in real production lines of special-shaped steel.

Automated deep learning system for power line inspection image analysis and processing: Architecture and design issues