The Discourse-Historical Approach of Identity Construction in Corporate Promotional Videos for External Publicity Image

Corporate identity construction of external publicity image is an important part of the development of enterprises.Based on Wodak’s discourse-historical approach,this study takes the text of COFCO’s English promotional video as the research object,analyzes the corporate brand image,media image,organizational image,and environmental image constructed by the enterprises from three steps:linguistic expression,discourse strategy,and theme to provide references for Chinese enterprises to enhance their international influence.

The motion analysis of fire video images based on moment features and flicker frequency

In this paper, motion analysis methods based on the moment features and flicker frequency features for early fire flame from ordinary CCD video camera were proposed, and in order to describe the changing of flame and disturbance of non-flame phenomena further more, the average changing pixel number of the first-order moments of consecutive flames has been defined in the moment analysis as well. The first-order moments of all kinds of flames used in our experiments present irregularly flickering, and their average changing pixel numbers of first-order moments are greater than fire-like disturbances. For the analysis of flicker frequency of flame, which is extracted and calculated in spatial domain, and therefore it is computational simple and fast. The method of extracting flicker frequency from video images is not affected by the catalogues of combustion material and distance. In experiments, we adopted two kinds of flames, i. e. , fixed flame and movable flame. Many comparing and disturbing experiments were done and verified that the methods can be used as criteria for early fire detection.

QoE Assessment and Prediction Method for HighDefinition Video Stream Using Image Damage Accumulation

The accuracy of the traditional assessment method of the quality of experience(Qo E) has been facing challenges with the growth of high-definition(HD) video streaming services.Image display-quality damage is the main factor that affects the Qo E in HD video services through UDP network transmission.In this paper,we introduce a novel objective factor known as image damage accumulation(IDA) to assess user's Qo E in HD video services.First,this paper quantitatively analyzed the effect on user quality of experience by IDA and established a mapping relationship between mean opinion scores and IDA.Furthermore,the probability of image damage caused by compression and transmission were analyzed.Based on this analysis,an objective Qo E assessment and prediction method for HD video stream service that evaluated the user experience according to IDA are proposed.The proposed method can achieve assessment and prediction accuracy on three distinct subjective tests.

A survey on image and video stitching

Image/video stitching is a technology for solving the field of view(FOV)limitation of images/videos.It stitches multiple overlapping images/videos to generate a wide-FOV image/video,and has been used in various fields such as sports broadcasting,video surveillance,street view,and entertainment.This survey reviews image/video stitching algorithms,with a particular focus on those developed in recent years.Image stitching first calculates the corresponding relationships between multiple overlapping images,deforms and aligns the matched images,and then blends the aligned images to generate a wide-FOV image.A seamless method is always adopted to eliminate such potential flaws as ghosting and blurring caused by parallax or objects moving across the overlapping regions.Video stitching is the further extension of image stitching.It usually stitches selected frames of original videos to generate a stitching template by performing image stitching algorithms,and the subsequent frames can then be stitched according to the template.Video stitching is more complicated with moving objects or violent camera movement,because these factors introduce jitter,shakiness,ghosting,and blurring.Foreground detection technique is usually combined into stitching to eliminate ghosting and blurring,while video stabilization algorithms are adopted to solve the jitter and shakiness.This paper further discusses panoramic stitching as a special-extension of image/video stitching.Panoramic stitching is currently the most widely used application in stitching.This survey reviews the latest image/video stitching methods,and introduces the fundamental principles/advantages/weaknesses of image/video stitching algorithms.Image/video stitching faces long-term challenges such as wide baseline,large parallax,and low-texture problem in the overlapping region.New technologies may present new opportunities to address these issues,such as deep learning-based semantic correspondence,and 3D image stitching.Finally,this survey discusses the challenges of image/video stitching and proposes potential solutions.

Digitalization of Underwater Video Image Using High Speed DSP Chip

This paper introduces a system based on Tls fifth generation DSP(Digital Signal Processor) device-TMS320C50 to construct the simplest system of digitalizing underwater video signal. The system realizes collecting 3 different density image data by means of software designation. The system may expand its outer data memory to 4 Giga byte by using a technology of memory page extension. Two different interface circuits for different speed peripheral devices and C50 are also designed: one is high speed A/D, and the other is static memory whose access time is 70ns. The system can digitalize analog video signal and process the gathered data in limited time.

Video learning based image classification method for object recognition

Automatic image classification is the first step toward semantic understanding of an object in the computer vision area.The key challenge of problem for accurate object recognition is the ability to extract the robust features from various viewpoint images and rapidly calculate similarity between features in the image database or video stream.In order to solve these problems,an effective and rapid image classification method was presented for the object recognition based on the video learning technique.The optical-flow and RANSAC algorithm were used to acquire scene images from each video sequence.After the selection of scene images,the local maximum points on comer of object around local area were found using the Harris comer detection algorithm and the several attributes from local block around each feature point were calculated by using scale invariant feature transform （SIFT） for extracting local descriptor.Finally,the extracted local descriptor was learned to the three-dimensional pyramid match kernel.Experimental results show that our method can extract features in various multi-viewpoint images from query video and calculate a similarity between a query image and images in the database.

Single-Phase Velocity Determination Based in Video and Sub-Images Processing:An Optical Flow Method Implemented with Support of a Programmed MatLab Structured Script

Important in many different sectors of the industry, the determination of stream velocity has become more and more important due to measurements precision necessity, in order to determine the right production rates, determine the volumetric production of undesired fluid, establish automated controls based on these measurements avoiding over-flooding or over-production, guaranteeing accurate predictive maintenance, etc. Difficulties being faced have been the determination of the velocity of specific fluids embedded in some others, for example, determining the gas bubbles stream velocity flowing throughout liquid fluid phase. Although different and already applicable methods have been researched and already implemented within the industry, a non-intrusive automated way of providing those stream velocities has its importance, and may have a huge impact in projects budget. Knowing the importance of its determination, this developed script uses a methodology of breaking-down real-time videos media into frame images, analyzing by pixel correlations possible superposition matches for further gas bubbles stream velocity estimation. In raw sense, the script bases itself in functions and procedures already available in MatLab, which can be used for image processing and treatments, allowing the methodology to be implemented. Its accuracy after the running test was of around 97% (ninety-seven percent);the raw source code with comments had almost 3000 (three thousand) characters;and the hardware placed for running the code was an Intel Core Duo 2.13 [Ghz] and 2 [Gb] RAM memory capable workstation. Even showing good results, it could be stated that just the end point correlations were actually getting to the final solution. So that, making use of self-learning functions or neural network, one could surely enhance the capability of the application to be run in real-time without getting exhaust by iterative loops.

Visibility Enhancement of Scene Images Degraded by Foggy Weather Condition: An Application to Video Surveillance

:In recent years,video surveillance application played a significant role in our daily lives.Images taken during foggy and haze weather conditions for video surveillance application lose their authenticity and hence reduces the visibility.The reason behind visibility enhancement of foggy and haze images is to help numerous computer and machine vision applications such as satellite imagery,object detection,target killing,and surveillance.To remove fog and enhance visibility,a number of visibility enhancement algorithms and methods have been proposed in the past.However,these techniques suffer from several limitations that place strong obstacles to the real world outdoor computer vision applications.The existing techniques do not perform well when images contain heavy fog,large white region and strong atmospheric light.This research work proposed a new framework to defog and dehaze the image in order to enhance the visibility of foggy and haze images.The proposed framework is based on a Conditional generative adversarial network(CGAN)with two networks;generator and discriminator,each having distinct properties.The generator network generates fog-free images from foggy images and discriminator network distinguishes between the restored image and the original fog-free image.Experiments are conducted on FRIDA dataset and haze images.To assess the performance of the proposed method on fog dataset,we use PSNR and SSIM,and for Haze dataset use e,r−,andσas performance metrics.Experimental results shows that the proposed method achieved higher values of PSNR and SSIM which is 18.23,0.823 and lower values produced by the compared method which are 13.94,0.791 and so on.Experimental results demonstrated that the proposed framework Has removed fog and enhanced the visibility of foggy and hazy images.

ADVANCES IN FRACTAL IMAGE AND VIDEO CODING

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RESEARCH ON KEY THECHNOLOGIES OF PORNOGRAPHIC IMAGE/VIDEO RECOGNITION IN COMPRESSED DOMAIN

Pornographic image/video recognition plays a vital role in network information surveillance and management. In this paper, its key techniques, such as skin detection, key frame extraction, and classifier design, etc., are studied in compressed domain. A skin detection method based on data-mining in compressed domain is proposed firstly and achieves the higher detection accuracy as well as higher speed. Then, a cascade scheme of pornographic image recognition based on selective decision tree ensemble is proposed in order to improve both the speed and accuracy of recognition. A pornographic video oriented key frame extraction solution in compressed domain and an approach of pornographic video recognition are discussed respectively in the end.

The Reality of Nigerian Image From the Perspective of The Home Videos

The home video through its offering plays pivotal roles of information, education and entertainment. It has provided knowledge to the viewing audience and directs their attention to issues to think about and/or learn. Popularly called Nollywood, the home video industry has brought scholars, reporters, reviewer, journalists, investors, and different kinds of people to the country; to investigate, invest, and observe the industry or network with people. Through the portrayals and representations of Nigeria and its people, a lot of people, especially foreigners and Nigerians in the Diaspora have come to understand the socio-economic and political terrain of the nation based on the home videos offerings; thus the need to x-ray the depictions in the Nigerian home video films to ascertain the reality of their Nigerian image from the perspectives. The study was undertaken through content analysis of 50 video films which were televised as programmes on television stations in Lagos and Africa Magic （a cable network station）, within the framework of agenda-setting and cultivation theories. The results reveal that while the home video producers have effectively revealed Nigerians as religious and traditional people, very little has been done to portray the economic and investment potentials of the nation; the nation＇s symbols like flags, coat of arm, currencies amongst others are barely revealed; negative attitudes of get-rich-quick, get-rich-at-all-cost, witchcraft, and fetish practices as well as violence, hooliganism, and ritualism amongst other things are often exaggerated in the films. Following the home video portrayals and representations, it could be imagined that the Nigerian urban environment is as beautiful and rich with predominantly affluent and flamboyant people as are depicted in the home videos. The misrepresentations, overrepresentations, and under-presentations of the nation＇s image in the home video can be very detrimental to the nation＇s socio-economic development especially as the nation＇s destiny is indirectly related to its image. They can further pose challenges to the attitudes and responses of people from other nations to the Nigerian citizens within and outside the country. Furthermore, some Nigerian citizens, especially the youths could aspire to and learn certain lifestyles and attitudes projected in the home videos as acceptable.

Detection and Selection of Moving Objects in Video Images Based on Impulse and Recurrent Neural Networks

The purpose of the article is to develop a methodology for automating the detection and selection of moving objects. The detection and separation of moving objects based on impulse and recurrence neural networks simulation. The result of the work is a developed motion detector based on impulse and recurrence neural networks and an automated system developed on the basis of this detector for detecting and separating moving objects and is ready for practical application. The feasibility of integrating the developed motion detector with Emgu CV (OpenCV) image processing package, multimedia framework functions, and DirectShow application programming interface were investigated. The proposed approach and software for the detection and separating of moving objects in video images using neural networks can be integrated into more sophisticated specialized computer-aided video surveillance systems, IoT (Internet of Things), IoV (Internet of Vehicles), etc.

Images of Women in Nigerian Home Videos： An Impact Assessment

This research is about the relationship between Nigerian home videos production, women and cultural ideologies. It is general agreed that there is a sexist problem which has dominated the entire mass media. The study researches that an impact assessment of the images of women in Nigerian home videos is designed to examine the sway Nigerian home videos portrayal of women have on women＇s position and status in the society. The study also investigates the influence of home videos on women＇s and girl＇s perception of themselves and its effect on their development potentials. With 300 respondents drawn from a select range of home videos viewers, a survey research was designed using Awka-urban, Capital of Anambra State, Nigeria as the research area and finds a negative perception of women as regards their image portrayal in the home videos by the viewers. However, this image portrayal has a negative effect on the development potentials of women and that of girl child and as well reflects on how women are seen and treated in Nigerian society.

Research on the Video Detection of Human Respiratory Motion Based on Sequential Images

Objective:Explore the feasibility of the high precision accelerometer for measuring the human respiratory displacement.Methods:A wireless acceleration acquisition system with the low power consumption and the high precision was designed with the high precision acceleration sensor ADXL355 as the core device.Based on the frequency characteristics of the breathing motion and the principle that the displacement can be calculated by the acceleration quadratic integration,two displacement measurement algorithms for the quasi-periodic weak motion are designed.Results:The simulation results show that the proposed algorithm is effective.The experimental results show that the designed acquisition system and algorithm can calculate the human respiratory displacement.Conclusion:The high precision accelerometer can be used to measure the human respiratory displacement,which provides a new method for the measurement of the human respiratory displacement.

The Influence of Short Video on City Image Dissemination in the New Media Era——Taking Tik Tok as an Example

With the popularity and rise of Chongqing,Chengdu,Xi’an and other cities on the short video platform,short video is increasingly becoming a new weapon for the construction and dissemination of the city image.Researching on the content,methods and effects of the hottest video APP Tik Tok,this paper adopts research methods of case analysis and text analysis to investigate how short videos promote the spread of urban image,and explore how they can enhance urban image transmission in the new media era in a better way.

IMAGE VIDEO8321电视自动播出系统

随着我国广播电视事业的迅猛发展，许多电视台都已安装或准备安装各种电视自动播控系统。同广泛采用的美国ＭＡＳＴＥＲ系列一样，加拿大ＩＭＡＧＥＶＩＤＥＯ系列也拥有愈来愈多用户群体。本文结合一例采用ＩＭＡＧＥＶＩＤＥＯ８３２１为播控切换台的自动播控系统，谈...

Strain field investigation of limestone specimen under uniaxial compression loads using particle image velocimetry

The particle image velocimetry (PIV) method was used to investigate the full-field displacements and strains of the limestone specimen under external loads from the video images captured during the laboratory tests.The original colorful video images and experimental data were obtained from the uniaxial compression test of a limestone.To eliminate perspective errors and lens distortion,the camera was placed normal to the rock specimen exposure.After converted into a readable format of frame images,these videos were transformed into the responding grayscale images,and the frame images were then extracted.The full-field displacement field was obtained by using the PIV technique,and interpolated in the sub-pixel locations.The displacement was measured in the plane of the image and inferred from two consecutive images.The local displacement vectors were calculated for small sub-windows of the images by means of cross-correlation.The video images were interrogated in a multi-pass way,starting off with 64×64 images,ending with 16×16 images after 6 iterations,and using 75% overlap of the sub-windows.In order to remove spurious vectors,the displacements were filtered using four filters:signal-to-noise ratio filter,peak height filter,global filter and local filter.The cubic interpolation was utilized if the displacements without a number were encountered.The full-field strain was then obtained using the local least square method from the discrete displacements.The strain change with time at different locations was also investigated.It is found that the normal strains are dependant on the locations and the crack distributions.Between 1.0 and 5.0 s prior to the specimen failure,normal strains increase rapidly at many locations,while a stable status appears at some locations.When the specimen is in a failure status,a large rotation occurs and it increases in the inverse direction.The strain concentration bands do not completely develop into the large cracks,and meso-cracks are not visible in some bands.The techniques presented here may improve the traditional measurement of the strain field,and may provide a lot of valuable information in investigating the deformation/failure mechanism of rock materials.

MOTION-BASED REGION GROWING SEGMENTATION OF IMAGE SEQUENCES

This paper proposes a motion-based region growing segmentation scheme for the object-based video coding, which segments an image into homogeneous regions characterized by a coherent motion. It adopts a block matching algorithm to estimate motion vectors and uses morphological tools such as open-close by reconstruction and the region-growing version of the watershed algorithm for spatial segmentation to improve the temporal segmentation. In order to determine the reliable motion vectors, this paper also proposes a change detection algorithm and a multi-candidate pro- screening motion estimation method. Preliminary simulation results demonstrate that the proposed scheme is feasible. The main advantage of the scheme is its low computational load.

Edge Oriented Compression Coding on Image Sequence

An edge oriented image sequence coding scheme is presented. On the basis of edge detecting, an image could be divided into the sensitized region and the smooth region. In this scheme, the architecture of sensitized region is approximated with linear type of segments. Then a rectangle belt is constructed for each segment. Finally, the gray value distribution in the region is fitted by normal forms polynomials. The model matching and motion analysis are also based on the architecture of sensitized region. For the smooth region we use the run length scanning and linear approximating. By means of normal forms polynomial fitting and motion prediction by matching, the images are compressed. It is shown through the simulations that the subjective quality of reconstructed picture is excellent at 0.0075 bit per pel.

Rapid Texture Mapping from Image Sequences for Building Geometry Model

An effective approach, mapping the texture for building model based on the digital photogrammetric theory, is proposed. The easily-acquired image sequences from digital video camera on helicopter are used as texture resource, and the correspondence between the space edge in building geometry model and its line feature in image sequences is determined semi-automatically. The experimental results in production of three-dimensional data for car navigation show us an attractive future both in efficiency and effect.