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.

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.

Video image mosaic via multi-module cooperation

We propose a video image mosaic method based on multi-module cooperation. This method stitches the video into a panorama with a large field of view, divided into three modules: the key frame selection module, the image mosaic module, and the optimization module. The key frame selection module obtains key frames by comprehensively evaluating the overlap rate and image quality. The image mosaic module stitches the key frames into a panoramic image to generate an initial mosaic result. The optimization module makes the mosaic result more natural and eliminates ghosts by using object detection advantages. Our method is tested on videos taken in real scenes, and the results have a more comprehensive and natural description.

MFSR: Maximum Feature Score Region-based Captions Locating in News Video Images

For news video images, caption recognizing is a useful and important step for content understanding. Caption locating is usually the first step of caption recognizing and this paper proposes a simple but effective caption locating algorithm called maximum feature score region （MFSR） based method, which mainly consists of two stages： In the first stage, up/down boundaries are attained by turning to edge map projection. Then, maximum feature score region is defined and left/right boundaries are achieved by utilizing MFSR. Experiments show that the proposed MFSR based method has superior and robust performance on news video images of different types.

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.

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.

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.

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.

An analysis of the uniformity of multi-fracture initiation based on downhole video imaging technology: A case study of Mahu tight conglomerate in Junggar Basin, NW China

To solve the problem that the production of Mahu conglomerate reservoir is not up to expectation after the multi-cluster plus temporary plugging fracturing technology is applied in horizontal wells, stages 2–6 in the test well MaHW6285 are selected to carry out erosion tests with different pumping parameters. The downhole video imaging technology is used to monitor the degree of perforations erosion, and then the fracture initiation and proppant distribution of each cluster are analyzed. The results showed that proppant entered 76.7% of the perforations. The proppant was mainly distributed in a few perforation clusters, and the amount of proppant entered in most of the clusters was limited. The proppant distribution in Stage 4 was relatively uniform, and the fracture initiation of each cluster in the stage is more uniform. The proppant distribution in stages 2, 3, 5, and 6 was significantly uneven, and the uniform degree of fracture initiation in each cluster is low. More than 70% of the proppant dose in the stage entered clusters near the heel end, so the addition of diverters did not promote the uniform initiation of hydraulic fractures. There was a positive correlation between the amount of proppant added and the degree of perforations erosion, and the degree of perforations erosion ranged from 15% to 352%, with an average value of 74.5%, which was far higher than the statistical results of shale reservoir tests in North America. The use of 180° phase perforation(horizontal direction) can reduce the “Phase Bias” of perforations erosion, promote uniform perforations erosion and fluid inflow. The research results provide the basis for optimizing the pumping procedure, reducing the perforation erosion and improving the success rate of diversion.

Temporal Shape Error Concealment for Video Objects

A novel temporal shape error concealment technique is proposed, which can he used in the context of object-based video coding schemes. In order to reduce the effect of the shape variations of a video object, the curvature scale space （CSS） technique is adopted to extract features, and then these features are used for boundary matching between the current frame and the previous frame. Because the temporal, spatial and sta- tistical video contour information are all considered, the proposed method can find the optimal matching, which is used to replace the damaged contours. The simulation results show that the proposed algorithm achieves better subjective, objective qualities and higher efficiency than those previously developed methods.

Efficient and High Accuracy 2-D DCT and IDCT Architecture for Image Compression Based on Improved CORDIC

Discrete Cosine Transform(DCT)is the most widely used technique in image and video compression.In this paper,the structure of DCT and Inverse DCT(IDCT)algorithm is split in the form of COordinate Rotation DIgital Computer(CORDIC)rotation matrix.The two-dimensional(2-D)8×8 DCT/IDCT units based on the improved rotation CORDIC algorithm is proposed.The shift and addition operations of the CORDIC algorithm are used to replace the cosine multiplication operations in the algorithm.The design does not contain any multiplier unit,which reduces the complexity of the hardware unit.The row-column transform unit composed of register arrays connects two 1-D 8-point DCT units to complete the calculation of 2-D 8×8 DCT.The pipeline latency of proposed architecture is 28 clock cycles.The proposed efficient two-dimensional DCT architecture has been synthesized on the Xilinx’s Kintex-7 FPGA.The resource utilization is 17.36%for Slice LUTs,3.49%for Slice Registers,and the maximum operating frequency is 172 MHz.It takes only 0.161μs to complete a process of block of 8×8 samples.A frame of image is processed by the designed DCT unit and then reconstructed by the IDCT unit to verify the function.The Peak Signal to Noise Ratio(PSNR)can reach 51.99 dB.

Development of a computer vision system to monitor pig locomotion

Avoiding lameness or leg weakness in pig production is crucial to reduce cost, improve animal welfare and meat quality. Detection of lameness detection by the use of vision systems may assist the farmer or breeder to obtain a more accurate and robust measurement of lameness. The paper presents a low-cost vision system for measuring the locomotion of moving pigs based on motion detection, frame-grabbing and multivariate image analysis. The first step is to set up a video system based on web camera technology and choose a test area. Secondly, a motion detection and data storage system are used to build a processing system of video data. The video data are analyzed measuring the properties of each image, stacking them for each animal and then analyze these stacks using multivariate image analysis. The system was able to obtain and decompose information from these stacks, where components could be extracted, representing a particular motion pattern. These components could be used to classify or score animals according to this pattern, which might be an indicator of lameness. However, further improvement is needed with respect to standardization of herding, test area and tracking of animals in order to have a robust system to be used in a farm environment.

Application of Active Contour Model in Tracking Sequential Nearshore Waves

In the present study, a generalized active contour model of gradient vector flow is combined with the video techniques of Argus system to delineate and track sequential nearshore wave crest profiles in the shoaling process, up to their breaking on the shoreline. Previous applications of active contour models to water wave problems are limited to controllable wave tank experiments. By contrast, our application in this study is in a nearshore field environment where oblique images obtained under natural and varying condition of ambient light are employed. Existing Argus techniques produce plane image data or time series data from a selected small subset of discrete pixels. By contrast, the active contour model produces line image data along continuous visible curves such as wave crest profiles. The combination of these two existing techniques, the active contour model and Argus methodologies, facilitates the estimates of the direction wave field and phase speeds within the whole area covered by camera. These estimates are useful for the purpose of inverse calculation of the water depth. Applications of the present techniques to Hsi-tzu bay where a beach restoration program is currently undertaken are illustrated. This extension of Argus video techniques provides new application of optical remote sensing to study the hydrodynamics and morphology of a nearshore environment.

Source extension based on ε-entropy

It is known by entropy theory that image is a source correlated with a certain characteristic of probability. The entropy rate of the source and ε- entropy (rate-distortion function theory) are the information content to identify the characteristics of video images, and hence are essentially related with video image compression. They are fundamental theories of great significance to image compression, though impossible to be directly turned into a compression method. Based on the entropy theory and the image compression theory, by the application of the rate-distortion feature mathematical model and Lagrange multipliers to some theoretical problems in the H.264 standard, this paper presents a new the algorithm model of coding rate-distortion. This model is introduced into complete test on the capability of the test model of JM61e (JUT Test Model). The result shows that the speed of coding increases without significant reduction of the rate-distortion performance of the coder.

3D displays: toward holographic video displays of 3D images

As the fiat panel displays （Liquid Crystal Displays, AMOLED, etc.） reach near perfection in their viewing qualities and display areas, it is natural to seek the next level of displays, including 3D displays. There is a strong surge in 3D liquid crystal displays as a result of the successful movie Avatar. Most of these 3D displays involve the employment of special glasses that allow one view perspective for each of the eyes to achieve a depth perception. Such displays are not real 3D displays. In fact, these displays can only provide one viewing perspective for all viewers, regardless of the viewer＇s position. In addition, a fundamental viewing problem of focusing and accommodation exist that can lead to discomfort and fatigue for many viewers. In this paper, the authors review the current status of stereoscopic 3D displays and their problems. The authors will also discuss the possibility of using fiat panels for the display of both phase and intensity of video image information, leading to the ultimate display of 3D holographic video images. Many of the fundamental issues and limitations will be presented and discussed.

FAST TEXT LOCATION BASED ON DISCRETE WAVELET TRANSFORM

The paper describes a texture-based fast text location scheme which operates directly in the Discrete Wavelet Transform (DWT) domain. By the distinguishing texture characteristics encoded in wavelet transform domain, the text is fast detected from complex background images stored in the compressed format such as JPEG2000 without full decompress. Compared with some traditional character location methods, the proposed scheme has the advantages of low computational cost, robust to size and font of characters and high accuracy. Preliminary experimental results show that the proposed scheme is efficient and effective.

Interactive mobile equipment safety task-training in surface mining

Improving the quality of equipment training for the Heavy Equipment Operators(HEO)is a critical task in improving safety and eliminating equipment-related injuries in mining.One of major responsibilities for the HEOs is proper machine inspection.Traditional miner safety training includes the use of hardcopy documents and video instructions.However,modern mobile and computer technology offers tremendous potential to improve the training process.In this study,we apply a 360-degree camera,opensource platform WordPress^(TM),and the software Unity3D in order to create materials and tools for the HEOs safety training to help trainees better understand the pre-shift safety machine inspection.The computer-based safety task training developed in this research is tested and implemented at a surface mine in the southern United States.

A robust system for real-time pedestrian detection and tracking

A real-time pedestrian detection and tracking system using a single video camera was developed to monitor pedestrians. This system contained six modules: video flow capture, pre-processing, movement detection, shadow removal, tracking, and object classification. The Gaussian mixture model was utilized to extract the moving object from an image sequence segmented by the mean-shift technique in the pre-processing module. Shadow removal was used to alleviate the negative impact of the shadow to the detected objects. A model-free method was adopted to identify pedestrians. The maximum and minimum integration methods were developed to integrate multiple cues into the mean-shift algorithm and the initial tracking iteration with the competent integrated probability distribution map for object tracking. A simple but effective algorithm was proposed to handle full occlusion cases. The system was tested using real traffic videos from different sites. The results of the test confirm that the system is reliable and has an overall accuracy of over 85%.

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.

Visual Ontology Construction for Digitized Art Image Retrieval

Current investigations on visual information retrieval are generally content-based methods. The significant difference between similarity in low-level features and similarity in high-level semantic meanings is still a major challenge in the area of image retrieval. In this work, a scheme for constructing visual ontology to retrieve art images is proposed. The proposed ontology describes images in various aspects, including type ＆ style, objects and global perceptual effects. Concepts in the ontology could be automatically derived. Various art image classification methods are employed based on low-level image features. Non-objective semantics are introduced, and how to express these semantics is given. The proposed ontology scheme could make users more naturally find visual information and thus narrows the “semantic gap”. Experimental implementation demonstrates its good potential for retrieving art images in a human-centered manner.