A Testbed for Automated Acquistion From a TEM

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.

VME image acquisition and processing using standard TV CCD cameras

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.

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.

영상 처리 및 컴퓨터 비전 분야에 있어서, 평균 제곱 오차(Mean Squared Error: MSE)는 좋은 수학적 특성(예를 들어, 척도성(metricability), 미분가능성(differentiability) 및 볼록 성질(convexity))을 가짐으로 인해 많은 영상 화질 최적화 문제의 객관적 척도로 사용되어 왔다. 그러나 MSE가 영상의 왜곡 신호에 대한 시각적 인지 화질과 상관도가 높지 않다는 것이 알려지면서, 이를 해결하기 위해 위에서 언급한 좋은 수학적 특성과 높은 영상 화질 예측 성능을 동시에 가지는 객관적 영상 화질 측정(Image Quality Assessment: IQA)척도가 활발히 연구되어 왔다. 비록 최근 제안된 좋은 수학적 성질을 만족시키는 IQA 척도들은 MSE와 비교하여 매우 향상된 주관적 화질 예측 성능을 보이지만, 상대적으로 높은 계산 복잡도를 가진다. 본 논문은 이를 해결하기 위해, 단순 라플라스 연산자를 이용한 좋은 수학적 특성을 가지는 새로운 IQA 척도를 제안한다. 제안 IQA 방법에 도입한 단순 라플라스 연산자는 인간 시각 체계의 망막에서의 광도 자극에 대한 시신경 반응을 효과적으로 모사할 뿐만 아니라 계산이 매우 단순하기 때문에, 제안 IQA 척도는 단순 라플라스 연산자를 사용하여 매우 빠른 계산 속도와 높은 주관적 화질 점수 예측력을 확보하였다. 제안 IQA 척도의 효과를 검증하기 위해, 최신 IQA 척도들과 광범위한 성능비교 실험을 수행하였다. 실험 결과, 제안하는 IQA 척도는 모든 테스트 IQA 척도들 중 MSE를 제외하고 가장 빠른 처리 속도를 보였을 뿐만 아니라, 가장 높은 주관적 화질예측 성능을 보였다. In image processing and computer vision fields, mean squared error (MSE) has popularly been used as an objective metric in image quality optimization problems due to its desirable mathematical properties such as metricability, differentiability and convexity. However, as known that MSE is not highly correlated with perceived visual quality, much effort has been made to develop new image quality assessment (IQA) metrics having both the desirable mathematical properties aforementioned and high prediction performances for subjective visual quality scores. Although recent IQA metrics having the desirable mathematical properties have shown to give some promising results in prediction performance for visual quality scores, they also have high computation complexities. In order to alleviate this problem, we propose a new fast IQA metric using a simple Laplace operator. Since the Laplace operator used in our IQA metric can not only effectively mimic operations of receptive fields in retina for luminance stimulus but also be simply computed, our IQA metric can yield both very fast processing speed and high prediction performance. In order to verify the effectiveness of the proposed IQA metric, our method is compared to some state-of-the-art IQA metrics. The experimental results showed that the proposed IQA metric has the fastest running speed compared the IQA methods except MSE under comparison. Moreover, our IQA metric achieves the best prediction performance for subjective image quality scores among the state-of-the-art IQA metrics under test.

Measurement of visual quality is of fundamental importance to numerous image and video processing applications. The goal of quality assessment (QA) research is to design algorithms that can automatically assess the quality of images or videos in a perceptually consistent manner. Image QA algorithms generally interpret image quality as fidelity or similarity with a "reference" or "perfect" image in some perceptual space. Such "full-reference" QA methods attempt to achieve consistency in quality prediction by modeling salient physiological and psychovisual features of the human visual system (HVS), or by signal fidelity measures. In this paper, we approach the image QA problem as an information fidelity problem. Specifically, we propose to quantify the loss of image information to the distortion process and explore the relationship between image information and visual quality. QA systems are invariably involved with judging the visual quality of "natural" images and videos that are meant for "human consumption." Researchers have developed sophisticated models to capture the statistics of such natural signals. Using these models, we previously presented an information fidelity criterion for image QA that related image quality with the amount of information shared between a reference and a distorted image. In this paper, we propose an image information measure that quantifies the information that is present in the reference image and how much of this reference information can be extracted from the distorted image. Combining these two quantities, we propose a visual information fidelity measure for image QA. We validate the performance of our algorithm with an extensive subjective study involving 779 images and show that our method outperforms recent state-of-the-art image QA algorithms by a sizeable margin in our simulations. The code and the data from the subjective study are available at the LIVE website.

The first quarter of 2007 started as an active season for the real-time image processing community. The annual SPIE Conference on Real-Time Image Processing, which was held in San Jose, CA, highlighted recent developments in this growing branch of image processing. As one of the few regular events with its focus matching that of JRTIP, one witnessed the growth in applications of real-time image and video processing. The conference served as an effective instrument to foster the dissemination of recent results and to leverage the cohesion of the real time image processing community. The preparations for the next SPIE Conference on Real-Time Image Processing in 2008 are already progressing and its call-for-papers is included at the end of this issue. In 2007, JRTIP is going to seek involvement of more scientists in the field of real-time image and video processing. After 1 year of operation, the editors-in-chief have started to recruit additional associate editors to enlarge the expertise base of the editorial board, to solicit manuscript submissions from potential authors, and to make the reviewing process more efficient. Interested colleagues should contact the editors-in-chief expressing their Associate Editor candidature in support of one or more fields within the focus of JRTIP. In addition, they wish to encourage researchers to act as guest editors for special issues on any real-time image or video processing related topics of interest to them. It is possible to schedule two special issues in 2007, provided that a draft call-for-papers is sent to the editors-in-chief as soon as possible. The third issue of JRTIP presents four articles, two are survey papers and two are original research papers. These articles address different real-time image processing perspectives ranging from algorithmic to hardware issues. The first survey paper deals with the real-time filtering in 2D and 3D using ordered statistics that are supported by a rich set of experimental results derived from several algorithmic variations. Performance measurements are used to demonstrate the effect of noise suppression and preservation of fine image structures and to show the DSP implementation of denoising filters. The second survey paper introduces a non-invasive analysis of dynamic processes in living cells using microscopic computer vision techniques for understanding the interactions between cellular and molecular functional units and for providing novel insights into the cell biology. The third article is an original research paper covering a machine vision application involving vision-based position sensing for aerial refueling of unmanned aerial vehicles in real-time. A full image processing chain is investigated and tested in a MATLAB/Simulink soft real-time environment as well as in a Linux/RTAI hard real-time environment. The feasibility of the real-time implementation is shown using off-the-shelf commercial hardware. The fourth article is another original research paper describing a hardware architecture for real-time fractal coding for image compression. The introduced parallel hardware architecture contains units for domain M. F. Carlsohn (&) Ingenieurberatung fur Computer Vision und Bildkommunikation, Am Heiddamm 36g, 28355 Bremen, Germany e-mail: matthias.carlsohn@t-online.de

This article describes a low‐cost image acquisition and processing system, which measures several yarn production characteristics, namely, the fibers twist orientation, the folded yarn twist step, the folded yarn twist orientation, and the existence of single (nonfolded yarn) or multiple cables (folded yarn). The imaging hardware consists of a USB web camera coupled to an analog microscope and a monochromatic light source. The acquired images are analyzed using custom designed software based on the IMAQ Vision image program from National Instruments. A full description of the developed image processing tool is presented, together with several experimental results. The results obtained are consistent with information deduced from high‐resolution images acquired using an electron microscope. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 391–399, 2010

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.

In the age of ever-increasing "-omics" studies, the accurate and statistically robust determination of microbial cell numbers within often-complex samples remains a key task in microbial ecology. Microscopic quantification is still the only method to enumerate specific subgroups of microbial clades within complex communities by, for example, fluorescence in situ hybridization (FISH). In this study, we improved an existing automatic image acquisition and cell enumeration system and adapted it for usage at high seas on board an oceanographic research ship. The system was evaluated by testing settings such as minimal pixel area and image exposure times ashore under stable laboratory conditions before being brought on board and tested under various wind and wave conditions. The system was robust enough to produce high-quality images even with ship heaves of up to 3 m and pitch and roll angles of up to 6.3°. On board the research ship, on average, 25% of the images acquired from plankton samples on filter membranes could be used for cell enumeration. Automated enumeration was highly correlated with manual counts (r(2) > 0.9). Even the smallest of microbial cells in the open ocean, members of the alphaproteobacterial SAR11 clade, could be confidently detected and enumerated. The automated image acquisition and cell enumeration system developed here enables an accurate and reproducible determination of microbial cell counts in planktonic samples and allows insight into the abundance and distribution of specific microorganisms already on board within a few hours.IMPORTANCE In this research article, we report on a new system and software pipeline, which allows for an easy and quick image acquisition and the subsequent enumeration of cells in the acquired images. We put this pipeline through vigorous testing and compared it to manual microscopy counts of microbial cells on membrane filters. Furthermore, we tested this system at sea on board a marine research vessel and counted bacteria on board within a few hours after the retrieval of water samples. The imaging and counting system described here has been successfully applied to a number of laboratory-based studies and allowed the quantification of thousands of samples and FISH preparations (see, e.g., H. Teeling, B. M. Fuchs, D. Becher, C. Klockow, A. Gardebrecht, C. M. Bennke, M. Kassabgy, S. Huang, A. J. Mann, J. Waldmann, M. Weber, A. Klindworth, A. Otto, J. Lange, J. Bernhardt, C. Reinsch, M. Hecker, J. Peplies, F. D. Bockelmann, U. Callies, G. Gerdts, A. Wichels, K. H. Wiltshire, F. O. Glöckner, T. Schweder, and R. Amann, Science 336:608-611, 2012, http://dx.doi.org/10.1126/science.1218344). We adjusted the standard image acquisition software to withstand ship movements. This system will allow for more targeted sampling of the microbial community, leading to a better understanding of the role of microorganisms in the global oceans.

Image quality is often lost during image acquisition, transmission, and compression. Therefore, image quality assessment (IQA) is crucial in image processing. Currently, image quality can be measured from the frequency domain features, but it only applicable to blurred grayscale images. Nevertheless, noise distortion is also a common problem in digital images, and colour also affects the perception of image quality. Therefore, this paper proposes an enhanced blur and noise specific colour image quality assessment that measures high-frequency components and image variance. The number of high-frequency components is related to the edge and noise. In order to distinguish the distortion of the image, the image variance estimation is included. Experiments on public databases have shown that this method outperforms PSNR and SSIM in terms of noise and blur distortion and has low processing time of 0.0941 s/img.

based on the idea of combining the embedded system with image processing, this paper designs an embedded image acquisition system, and separately designs and implements its hardware, software, WEB management module and the system function modules. The image acquisition system can carry out remote management by the user host through the WEB, capture target image and process in accordance with the relevant setting parameters. The whole design fully takes into account the general nature of the image acquisition system, which makes the system can be used as a generic image acquisition hardware platform, thus has good scalability.

Artificial Intelligence (AI) is the enhancement and method of computer system that handles tasks which requires human like intelligence such as recognition, language translation and visual interpretation. Subjective image quality assessment (IQA) is difficult to be implemented in real-time systems, methodology for enhancing the involvement in producing IQA model is to improve the quality of image by significant evaluation. Intuitively, human eyes are not sensitive to the distortion and damage from the area with lesser visual saliency (VS), VS is closely related to IQA. With this consideration, an effective IQA was proposed, which involved two processes. The local quality map of a distorted image was computed using the structural similarity function of its feature attributes, such as brightness, chrominance and gradient. Second, the local quality map was weighted with visual saliency (VS) to get the objective evaluation of image quality. The VS was modeled by extracting the saliency of low-level features of the image, wiping off the molestation information from these saliency based on an apriori threshold, and combining the effective information to construct the saliency map. Image processing using fuzzy is gathering features and segments as fuzzy set while processing images. The experiments on the two largest database for six classical IQA metrics demonstrate that performance of weighted-VS IQA metrics is superior to the performance of no weighted-VS IQA metrics, and the proposed IQA method has higher computational accuracy than the other IQA metrics under a moderate computational complexity, especially for two types of distortion images, such as local block-wise (Block) and fast-fading (FTF).

The acquisition of high resolution images in atomic force microscopy (AFM) is correlated to the cantilever's tip shape, size, and imaging conditions. In this work, relative tip wear is quantified based on the evolution of a direct experimental observable in amplitude modulation atomic force microscopy, i.e., the critical amplitude. We further show that the scanning parameters required to guarantee a maximum compressive stress that is lower than the yield/fracture stress of the tip can be estimated via experimental observables. In both counts, the optimized parameters to acquire AFM images while preserving the tip are discussed. The results are validated experimentally by employing IgG antibodies as a model system.

STEM role in failure analysis