Decoding brain responses to pixelized images in the primary visual cortex: implications for visual cortical prostheses

Visual cortical prostheses have the potential to restore partial vision. Still limited by the low-resolution visual percepts provided by visual cortical prostheses, implant wearers can currently only ＂see＂ pixelized images, and how to obtain the specific brain responses to different pixelized images in the primary visual cortex（the implant area） is still unknown. We conducted a functional magnetic resonance imaging experiment on normal human participants to investigate the brain activation patterns in response to 18 different pixelized images. There were 100 voxels in the brain activation pattern that were selected from the primary visual cortex, and voxel size was 4 mm × 4 mm × 4 mm. Multi-voxel pattern analysis was used to test if these 18 different brain activation patterns were specific. We chose a Linear Support Vector Machine（LSVM） as the classifier in this study. The results showed that the classification accuracies of different brain activation patterns were significantly above chance level, which suggests that the classifier can successfully distinguish the brain activation patterns. Our results suggest that the specific brain activation patterns to different pixelized images can be obtained in the primary visual cortex using a 4 mm × 4 mm × 4 mm voxel size and a 100-voxel pattern.

Visually meaningful image encryption algorithm based on digital signature

Traditional image encryption algorithms transform a plain image into a noise-like image.To lower the chances for the encrypted image being detected by the attacker during the image transmission,a visually meaningful image encryption scheme is suggested to hide the encrypted image using another carrier image.This paper proposes a visually meaningful encrypted image algorithm that hides a secret image and a digital signature which provides authenticity and confidentiality.The recovered digital signature is used for the purpose of identity authentication while the secret image is encrypted to protect its confidentiality.Least Significant Bit(LSB)method to embed signature on the encrypted image and Lifting Wavelet Transform(LWT)to generate a visually meaningful encrypted image are designed.The proposed algorithm has a keyspace of 139.5-bit,a Normalized Correlation(NC)value of 0.9998 which is closer to 1 and a Peak Signal to Noise Ratio(PSNR)with a value greater than 50 dB.Different analyses are also performed on the proposed algorithm using different images.The experimental results show that the proposed scheme is with high key sensitivity and strong robustness against pepper and salt attack and cropping attack.Moreover,the histogram analysis shows that the original carrier image and the final visual image are very similar.

Realizing precision pulse TIG welding with arc length control and visual image sensing based weld detection

Methods of arc length control and visual image based weld detection for precision pulse TIG welding were investigated. With a particular all hardware circuit, arc voltage during peak current stage is sampled and integrated to indicate arc length, deviation of arc length and adjusting parameters are calculated and output to drive a step motor directly. According to the features of welding image grabbed with CCD camera, a special algorithm was developed to detect the central line of weld fast and accurately. Then an application system were established, whose static arc length error is ±0.1 mm with 20 A average current and 1 mm given arc length, static detection precision of weld is 0.01 mm , processing time of each image is less than 120 ms . Precision pulse TIG welding of some given thin stainless steel components with complicated curved surface was successfully realized.

From Physical Space to Visual Image Space

The theoretical framework of visual simulation in virtual reality is discussed. The new concept of visual image space is supposed. On the basis of visual image space, in visual perceptive sense, VR is considered as a spatial simulation. The objective of the spatial simulation is to transform physical space to visual image space. Last, the prototype system, surveying & mapping virtual Reality (SMVR), is developed, and the space simulation above is realized. By use of SMVR, the real 3D representation, 3D visual analysis, virtual plan and designs can be implemented.

Dynamic Visual Image Modeling Based on Mobile RobotSelf- Organizing Network in Internetof Things Perception Layer

The dynamic multichannel binocular visual image modeling is studied based on Internet of Things (IoT) Perception Layer, using mobile robot self-organizing network. By employing multigroup mobile robots with binocular visual system, the real visual images of the object will be obtained. Then through the mobile self-organizing network, a three-dimensional model is rebuilt by synthesizing the returned images. On this basis, we formalize a novel algorithm for multichannel binocular visual three-dimensional images based on fast three-dimensional modeling. Compared with the method based on single binocular visual system, the new algorithm can improve the Integrity and accuracy of the dynamic three-dimensional object modeling. The simulation results show that the new method can effectively accelerate the modeling speed, improve the similarity and not increase the data size.

Expression Mechanism of Chinese Visual Experience Taking the Historical Evolvement and Extraterritorial Construction of the Visual Image of Sun Wukong as an Example

As typical visual culture symbol of China, the visual image of Sun Wukong firstly appeared on the mural of Yulin Caves of Dunhuang in Western Xia regime and the story of Monk Tang and his prentices on the mural in Yuan Dynasty. Up to Yuan Dynasty, it became very popular. Since the novel Pilgrimage to the West was published, the visual image of Sun Wukong has appeared in the visual carriers of wood block, colored drawing, paper-cut, traditional Chinese opera, film, television, ad, cartoon and so on. European countries, America, Japan and South Korea use advanced film and TV technology and digital technology to deduce, model, adapt and simulate the visual image of Sun Wukong. This paper investigates the construction of the visual image of Sun Wukong in China and extraterritorial countries and regions, tries to explore Chinese ＂visual＂ experience in mediaeval times and especially modern times and seeks a clue for understanding Chinese problem of visual expression.

Visual positioning of rectangular lead components based on Harris corners and Zernike moments

With the increasing necessities for reliable printed circuit board(PCB) product, there has been a considerable demand for high speed and high precision vision positioning system. To locate a rectangular lead component with high accuracy and reliability, a new visual positioning method was introduced. Considering the limitations of Ghosal sub-pixel edge detection algorithm, an improved algorithm was proposed, in which Harris corner features were used to coarsely detect the edge points and Zernike moments were adopted to accurately detect the edge points. Besides, two formulas were developed to determine the edge intersections whose sub-pixel coordinates were calculated with bilinear interpolation and conjugate gradient method. The last experimental results show that the proposed method can detect the deflection and offset, and the detection errors are less than 0.04° and 0.02 pixels.

Analysis of Fabric's Visual Image Based on Seasonal Application to Clothing

Fabric’s visual image is on important that affects its seasonal application to clothing. In this paper, color and luster property of the fabric were simultaneously considered to elaborate application to clothing in seasons. Fabric samples were selected in the four seasons, which were quantified by using the Muncell color system. The data of the color attributes and fabric’s surface luster property were analyzed, which applied in spring, summer, autumn and winter.

Recent Advances and Challenges of Visual Signal Quality Assessment

While quality assessment is essential for testing, optimizing, benchmarking, monitoring, and inspecting related systems and services, it also plays an essential role in the design of virtually all visual signal processing and communication algorithms, as well as various related decision-making processes. In this paper, we first provide an overview of recently derived quality assessment approaches for traditional visual signals (i.e., 2D images/videos), with highlights for new trends (such as machine learning approaches). On the other hand, with the ongoing development of devices and multimedia services, newly emerged visual signals (e.g., mobile/3D videos) are becoming more and more popular. This work focuses on recent progresses of quality metrics, which have been reviewed for the newly emerged forms of visual signals, which include scalable and mobile videos, High Dynamic Range (HDR) images, image segmentation results, 3D images/videos, and retargeted images.

The Dissemination of the Visual Image ofWhuhan Tianhe Airport Terminal Under Urban Cultural

With the vigorous development of China＇ s civil aviation industry and the advertising industry in recent years, airport image as a ＂commanding city height＂ has increasingly attracted attention of many as an ideal place for advertising and corporation image display. Airport advertising communication constitutes audience including government officials, high-level policy makers, corporate travel managers and travelers, in which high-income earners and foreign guests take a higher proportion. Airport advertising （on free media and aviation propaganda machine business supplies media） main involves two categories： outdoor advertising on the airport perimeter and expressway and advertising inside the terminal. In a broad sense, they all belong to the category of outdoor advertising.

Machine learning based fileless malware traffic classification using image visualization

In today's interconnected world,network traffic is replete with adversarial attacks.As technology evolves,these attacks are also becoming increasingly sophisticated,making them even harder to detect.Fortunately,artificial intelli-gence(Al)and,specifically machine learning(ML),have shown great success in fast and accurate detection,classifica-tion,and even analysis of such threats.Accordingly,there is a growing body of literature addressing how subfields of Al/ML(e.g.,natural language processing(NLP))are getting leveraged to accurately detect evasive malicious patterns in network traffic.In this paper,we delve into the current advancements in ML-based network traffic classification using image visualization.Through a rigorous experimental methodology,we first explore the process of network traffic to image conversion.Subsequently,we investigate how machine learning techniques can effectively leverage image visualization to accurately classify evasive malicious traces within network traffic.Through the utilization of production-level tools and utilities in realistic experiments,our proposed solution achieves an impressive accuracy rate of 99.48%in detecting fileless malware,which is widely regarded as one of the most elusive classes of malicious software.

Weld pool image sensor for pulsed MIG welding

Visual image sensor is developed to detect the weld pool images in pulsed MIG welding. An exposure controller, which is composed of the modules of the voltage transforming, the exposure parameters presetting, the complex programmable logic device （CPLD） based logic controlling, exposure signal processing, the arc state detecting, the mechanical iris driving and so on, is designed at first. Then, a visual image sensor consists of an ordinary CCD camera, optical system and exposure controller is established. The exposure synchronic control logic is described with very-high-speed integrated circuit hardware description language （VHDL） and programmed with CPLD , to detect weld pool images at the stage of base current in pulsed MIG welding. Finally, both bead on plate welding and V groove filled welding are carried out, clear and consistent weld pool images are acquired.

Acquisition and processing of coaxial image of molten pool and keyhole in Nd:YAG laser welding with high power

An experimental setup of acquiring the coaxial visual image of the molten pool and keyhole in high power Nd:YAG laser welding is introduced in this paper. It is one of the most difficult problems in acquiring coaxial image that the coaxial imaging signal of molten pool and keyhole must be separated from the laser beam with high power. This problem was resolved by designing a dichroitic spectroscope. The characteristics of imaging signal were analyzed and the coaxial image of molten pool and keyhole was acquired. A smoothing filter and a homomorphic filter were designed to remove the low frequency noise and to enhance the image according to the characteristics of imaging signal. At last, edges of molten pool and keyhole were detected and extracted based on image segmentation with threshold.

In vivo assessment of structural changes of the urethra in lower urinary tract disease using cross-polarization optical coherence tomography

The paper presents the results of a study of the female urethra in cases of urethral pain syndrome(UPS)and inflammatory diseases of the lower urinary tract using cross-polarization optical coherence tomography(CP OCT).Urethral wall structure was studied in 86 patients;233 CP OCT images were collected.A comparative qualitative analysis of three groups of CP OCT images—"norm","Inflammation"and"UPS"—identified that despite the absence of a clear inflammatory factor in the patient's examination,the urethral tissues in UPS were in an altered state.The changes in the urethral wall with UPS and in cases of inflammation were similar.Using a point scale,three experts independently performed visual scoring of the CP OCT images.Three parameters:epithelial contrast,cavities and the minimum signal depth in the co-channel were evaluated.It was found that,individually,the parameters correlate only weakly with the diag-nosis.Area under the receiver operating characteristic(ROC)curve was from 0.51 to 0.78.The joint use of a number of visual signs has a greater diagnostic value than the use of the criteria individually.Area under the ROC curve using the developed cumulative criterion reached up to 0.87-0.89.This study could form the basis of a scoring system for assessing the state of the urethral tract using CP OCT images in real time.The CP OCT method provides information on the state of urethral tissues that cannot be obtained with traditional cystoscopy.

CI Strategy Research of Agriculture Creative Industrial Park in Langfang

By studying developing status and trends of agricultural industrial park in Langfang, the paper will make an analysis of the present development and main factors which restrict the development of CI strategy in agricultural creative industrial park in Langfang city. The paper also tends to put forward the measures to speed up the CI strategy in Langfang city industrial park and to form a new pattern with local characteristics and advantages.

Imaging for Minimally Invasive Surgery

The successful outcome of any minimally invasive procedure is highly dependent on the imaging chain, as the medical team has to rely on indirect visualization of the surgical field during the entire procedure. During the last decade, the quality of the images obtainable pre- and intraoperatively has evolved significantly. In addition to the introduction of intra-operative image acquisition techniques such as ultrasound, X-ray, CT or MR, optical imaging technology as well as the corresponding processing units have undergone a rapid development. The article will review the activity related to minimally invasive procedures at the Operating Rooms of the Future (FOR) at St. Olavs Hospital, University Hospital of Trondheim, Norway. The imaging related demands of several surgical fields are introduced and the evolution of the imaging and visualization techniques at FOR will be presented. Subsequently, ongoing research projects in a dedicated visualization laboratory will be discussed and the advantages of updating the imaging equipment continuously in order to keep up with the latest developments in the field will be presented. It will be shown that the quality of the image acquisition and display can be significantly improved when compared to today’s standard. In addition to increasing the surgeon’s confidence, better imaging will lead to increased patient safety as well as more efficient interventions.

Visual interactive image clustering:a target-independent approach for configuration optimization in machine vision measurement

Machine vision measurement(MVM)is an essential approach that measures the area or length of a target efficiently and non-destructively for product quality control.The result of MVM is determined by its configuration,especially the lighting scheme design in image acquisition and the algorithmic parameter optimization in image processing.In a traditional workflow,engineers constantly adjust and verify the configuration for an acceptable result,which is time-consuming and significantly depends on expertise.To address these challenges,we propose a target-independent approach,visual interactive image clustering,which facilitates configuration optimization by grouping images into different clusters to suggest lighting schemes with common parameters.Our approach has four steps:data preparation,data sampling,data processing,and visual analysis with our visualization system.During preparation,engineers design several candidate lighting schemes to acquire images and develop an algorithm to process images.Our approach samples engineer-defined parameters for each image and obtains results by executing the algorithm.The core of data processing is the explainable measurement of the relationships among images using the algorithmic parameters.Based on the image relationships,we develop VMExplorer,a visual analytics system that assists engineers in grouping images into clusters and exploring parameters.Finally,engineers can determine an appropriate lighting scheme with robust parameter combinations.To demonstrate the effiectiveness and usability of our approach,we conduct a case study with engineers and obtain feedback from expert interviews.

MultiSciView: Multivariate Scientific X-ray Image Visual Exploration with Cross-Data Space Views

X-ray images obtained from synchrotron beamlines are large-scale,high-resolution and high-dynamic-range grayscale data encoding multiple complex properties of the measured materials.They are typically associated with a variety of metadata which increases their inherent complexity.There is a wealth of information embedded in these data but so far scientists lack modem exploration tools to unlock these hidden treasures.To bridge this gap,we propose MultiSciView,a multivariate scientific x-ray image visualization and exploration system for beamline-generated x-ray scattering data.Our system is composed of three complementary and coordinated interactive visualizations to enable a coordinated exploration across the images and their associated attribute and feature spaces.The first visualization features a multi-level scatterplot visualization dedicated for image exploration in attribute,image,and pixel scales.The second visualization is a histogram-based attribute cross filter by which users can extract desired subset patterns from data.The third one is an attribute projection visualization designed for capturing global attribute correlations.We demonstrate our framework by ways of a case study involving a real-world material scattering dataset.We show that our system can efficiently explore large-scale x-ray images,accurately identify preferred image patterns,anomalous images and erroneous experimental settings,and effectively advance the comprehension of material nanostructure properties.

Image understanding, attention and human early visual cortex

This paper reviews our recent fMRI and psychophysical finding on： 1） perceived size represen- tation in V1; 2） border ownership representation in V2; and 3） neural processing of partially occluded face. These findings demonstrate that the human early vi- sual cortex not only performs local feature analyses, but also contributes significantly to high-level visual computation with assistance of attention-enabled cortical feed- back. Moreover, by taking advantage of recent findings on early visual cortex from neuroscience and cognitive science, we build a biologically plausible attention model that can well predict human scanpaths on natural images.

Development of a smart city planning support tool using the cooperative method

A reduction of environmental burdens is currently required. In particular, proposing a new approach for the construction of a smart city using renewable energy is important. The technological development of a smart city is founded building equipment and infrastructure. However, planning methods and their techniques using the collaboration approach with residents are only just developing. This study aimed to develop a support tool for the construction of a smart city using renewable energy while facilitating consensus-building efforts among residents using the method for a cooperative housing development. We organized the supporting methods for the construction of residential area using the cooperative method. Then, we developed supporting toots that interface the computer with these methods. We examined the support techniques for the construction of a residential area using renewable energy technology by analyzing Japanese cases of a smart city. Moreover, we developed a support toot for the construction of a smart city on a trial basis. We integrated the smart city construction toots and the cooperative housing construction support tool. This tool has a 3D modeling system that helps residents to easily understand the space image as a result of the examination. We also developed a professional supporting toot that residents can consider for cost-effectiveness in renewable energy and its environmental toad reduction rate for the planning of a smart city.