Parallel Processing Algorithms of Ultrasound Images

In order to determine the number and depth of grooves in a grooved acetate filter rod,a method based on digital image processing technology was proposed.Aiming at the irregular shape of the end slice of the filter rod,a complementary image fusion algorithm was designed to improve the recognition rate and accuracy of characteristic region.The results indicated that this method completely met the requirements for determination of characteristic parameters of grooved filter rod,the determination accuracy of groove depth was up to 0.01 mm.

The history of Chinese ceramics has become the representative of southern ceramics with its unique celadon carving, black glaze mining, painting, printing and other decorative styles. Minnan architectural ceramics are fresh carriers, samples and memories of Chinese cultural symbols and aesthetic habits. Based on the digital image processing technology, this paper analyzes the decorative patterns of southern Fujian architectural ceramics, introduces the digital image calibration principle and sampling quantification method used in the decorative patterns of southern Fujian architectural ceramics, and then uses image segmentation and binarization analysis, color digital image processing and analysis technology to discover the abstract beauty of Minnan ceramic ornamentation.

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.

The quality of optics' surface is of an important character which has critical influence in optical system. There are many ways to detect surface quality, but interferometry is considered as an effective technology. Interfere fringes which obtained from our experiment based on equal thickness interference were processed with digital image processing (DIP) technology in this paper. Image smoothing, fringes thinning, fringes' space measurement and P-V value measurement were done in this processing, Which can give optics' surface information automatically and accurately. We measured some optics whose apertures are not more than 30mm, and the result is satisfactory. Our method will be widely used in industrial inspection, especially in optical works in the future.

This paper which is based on digital image process technology, with LabVIEW and IMAQ Vision,designs a effective method about image acquisition and processing. The system achieve image acquisition,save,playback,gray transformation,denoise,threshold segmentation ,template matching and calculation the center of the target lacation.Virtual Instrument which own flexible hardware and software,has greatly enhanced efficiency and accuracy.

Object detection is a hot topic in the field of machine vision. In the innovation and development of modern technology, the integration of machine learning, pattern recognition, image processing and other multidisciplinary knowledge can effectively solve the image problem. In computer vision and digital image processing technology in the development of innovation, target detection theory research and practical application has achieved excellent results, although there are many problems need to solve, but a lot of new technology and new method has yet to be developed, so countries scholars gradually strengthen the scientific research strength, strong adaptability are put forword technique, high precision and good robustness. In this paper, based on the understanding of the research status of object detection, according to the basic theory of image processing, the application of computer vision in object detection is analyzed. The final experimental results show that shadow detection, image enhancement and filtering methods can effectively improve the application effect.

With the development of electronic technology, computer software and hardware technology, image processing and technology related to human vision, the technology of machine vision image processing has also achieved rapid development. With the rapid development of science and technology, digital image processing technology has been widely used in various fields, among which image segmentation is an extremely important technology. Image segmentation is an important intermediate technology in digital image processing. It relies on the underlying technology of image digital processing to serve high-level applications such as pattern recognition. Processing the information interaction between machine and the real world is the first step in the study of artificial intelligence, and the goal of computer vision research is to make the computer have the ability to perceive and understand image information similar to human. This paper expounds the basic principle of image segmentation technology, analyzes and discusses the methods of image segmentation, and studies the application of image segmentation technology in digital image processing.

Interest in digital image processing methods stems from two principal application areas: improvement of pictorial information for human interpretation; and processing of image data for storage, transmission, and representation for autonomous machine perception. Computer digital image technology is a very important branch of the computer application discipline, and its application areas include measurement, computer-aided design, physics, three-dimensional simulation and other industries. Moreover, with the improvement of computer hardware performance, image processing algorithms have improved the application of digital image processing technology. This Review article focuses on the current digital image processing technology and its application in Medical, forest protection and other fields of today’s interest.

Talus deposit is often seen in the hydropower projects in the southwest of China. Its mechanical properties are so complex that microscopic structure study is often used to reveal the essence of deformation and damage. The digital image processing technology (DIPT) is introduced to the discrete element simulation of talus deposits. Based on the study of DIPT, a Photo-To-PFC (PTP) automodeling program is developed. It is able to realize the whole process: analyzing and processing the digital image, acquiring the information and establishing the model files. The discrete element model of talus deposit can be established fast and correctly by the PTP from the digital photo on-site. A new way is opened up for the study of the talus deposit. As an example, some talus deposit data of Gushui hydropower station is used, structure model and mechanical properties of talus deposit are studied based on DIPT and PTP. The mechanical properties are studied by the numerical simulation of biaxial compression test. The results show that the gravels and soil mass compress with each other to form a corporate load-carrying body for sharing the external forces. The stress-strain curves show a strain-hardening stage obviously due to the impact of gravels. With the increasing of bond strength among soil particles, the initial elastic modulus and peak strength of talus deposit go up at a certain level; the initial elastic modulus and peak strength increase a lot as the existence of gravels.

Traditional k out of n threshold visual cryptography scheme is proposed to hide a secret image into n shares, where only k or more shares can visually reveal the secret image. Most of the previous state of art approaches on visual cryptography are almost restricted in processing of binary images as secret, which are inadequate for many applications like securely transmission of medical images(Store and Forward Telemedicine), forensic images etc. In this paper, a new Verifiable Multi-toned Visual Cryptography (VMVC) scheme is proposed to securely transmit the confidential images on web. Proposed approach also provides cheating prevention, since each pixel of shares contains a self embedding verifiable bit for integrity test of that pixel. Many existing approaches are suffering from many unnecessary encryption constraints like random shares, codebook requirement, contrast loss etc, which all are successfully addressed in proposed approach. Some comparisons with previously proposed methods are also made. Experimental results and analysis are used to prove the efficiency of proposed approach.

In order to speedup image processing in embedded environment, we construct a parallel processing system of images. The parallel processing system includes a parallel hardware, a new defined language for parallel image processing and a set of software tools. From the view of high performance, low power dissipation and the characteristics of image processing, we construct a SIMD coprocessor as an image processing accelerator. Using a RISC host processor manages the whole system. The SIMD processor is scalable. We also define a new language which is extended from standard C. A new data type and a new keyword kernel are added to the language to explicitly describe parallelism. For the new hardware and language of parallel image processing, we also research software tools for this parallel system. The software tools maps programs to code that runs on the new hardware. For example develop a scheduler to transfer stream data between memories and register files. From the analysis we found that the parallel image processing system can not only match image applications' characteristics but also easy to implement by using VLSI technology. With new language and software tools supporting, an embedded real-time parallel image processing system becomes available for programmers.

The major studied in this dissertation is the non-destructive testing method of silkworm cocoon's quality, based on the digital image processing and photoelectricity technology. Through the images collection and the data analysis, procession and calculation of the tested silkworm cocoons with the non-destructive testing technology, internet applications automatically reckon all items of the classification indexes. Finally we can conclude the classification result and the purchase price of the silkworm cocoons. According to the domestic classification standard of the silkworm cocoons, the author investigates various testing methods of silkworm cocoons which are used or have been explored at present, and devices a non-destructive testing scheme of the silkworm cocoons based on the digital image processing and photoelectricity technology. They are dissertated about the project design of the experiment. The precisions of all the implements are demonstrated. I establish Manifold mathematic models, compare them with each other and analyze the precision with technology of databank to get the best mathematic model to figure out the weight of the dried silkworm cocoon shells. The classification methods of all the complementary items are designed well and truly. The testing method has less error and reaches an advanced level of the present domestic non-destructive testing technology of the silkworm cocoons.

We present MOPEX - a software package for astronomical image processing and display. The package is a combination of command-line driven image processing software written in C/C++ with a Java-based GUI. The main image processing capabilities include creating mosaic images, image registration, background matching, point source extraction, as well as a number of minor image processing tasks. The combination of the image processing and display capabilities allows for much more intuitive and efficient way of performing image processing. The GUI allows for the control over the image processing and display to be closely intertwined. Parameter setting, validation, and specific processing options are entered by the user through a set of intuitive dialog boxes. Visualization feeds back into further processing by providing a prompt feedback of the processing results. The GUI also allows for further analysis by accessing and displaying data from existing image and catalog servers using a virtual observatory approach. Even though originally designed for the Spitzer Space Telescope mission, a lot of functionalities are of general usefulness and can be used for working with existing astronomical data and for new missions. The software used in the package has undergone intensive testing and benefited greatly from effective software reuse. The visualization part has been used for observation planning for both the Spitzer and Herschel Space Telescopes as part the tool Spot. The visualization capabilities of Spot have been enhanced and integrated with the image processing functionality of the command-line driven MOPEX. The image processing software is used in the Spitzer automated pipeline processing, which has been in operation for nearly 3 years. The image processing capabilities have also been tested in off-line processing by numerous astronomers at various institutions around the world. The package is multi-platform and includes automatic update capabilities. The software package has been developed by a small group of software developers and scientists at the Spitzer Science Center. It is available for distribution at the Spitzer Science Center web page.

In order to establish a set of tree height measuring system, on the basis of digital image processing, this paper discusses a new method. An ordinary digital camera was used to get tree photos and two marker points were chosen in the camera's field of view on the tree. One marker point was set on the root of the tree; the other was set one meter high from the root. A tripod was used to fix the camera for taking photos of the tree. It made the photo perpendicular to the ground. The computer may extract the coordinates of the two marker points and the top point according to their color features during image processing. Lastly, the tree height can be worked out using triangle similarity theory. The experimental results indicate that the relative measurement error of tree height is about 4%. So it is a viable method.

Nowadays, the world suffers from a terrible problem with COVID-19. Some researchers worked for a facemask detection biometric system by using Residual Networks such as Resnet50 or Resnet100. This research focuses on depreciating the transmission of Corona Virus Disease (COVID) from person to person. To wear a facemask plays an excellent role in not spreading COVID to the community. Moreover, to enhance social life, automatic facemask detection and facemask recognition systems are needed. Additionally, this system is helpful for security enhancement through face recognition. Here, the research for developing and implementing a biometric system for banks, offices, universities, and other public areas. This system helps in detecting the facemask for wearing by the human With Artificial Intelligence (AI), Deep Learning (DL), and Digital Image Processing technologies, this system allows the person to enter inside or stay outside because of not wearing a facemask. Besides designing and implementing a new model, the authors will discuss pre-defined the VGG16 deep learning model of CNN (Convolution Neural Network). Further, conclude the performance of both CNN models. This paper proposes a Facemask Detection model for solving the problem of manual care. This proposed model is a combination of most trending technologies such as AI, DL, and Image processing. In the future, describe this newly implemented model by appending Gaussian noise with images and make the system more reliable for actual use.KeywordsCOVID-19FacemaskFace detectionBiometric systemArtificial Intelligence (AI)