AVI Format Research Articles

Forensic integrity verification of video recordings based on MTS files.

Digital video is used in criminal trials as evidence with legal responsibility because video content vividly depicts events occurring at a crime scene. However, using sophisticated video editing software, assailants can easily manipulate visible clues for their own benefit. Therefore, the integrity of digital video files acquired or submitted as evidence must be ensured. Forensic analysis of digital video is key to ensuring the integrity of links with individual cameras. In this study, we analyzed whether it is possible to ensure the integrity of MTS video files. Herein, we propose a method to verify the integrity of MTS files encoded by advanced video coding high definition (AVCHD), which is frequently used for video recording. To verify MTS file integrity, we propose five features. Codec information, picture timing, and camera manufacture/model are modified AVI and MP4-like format video verification features. Group of pictures and Universally Unique Identifier patterns were specifically developed for MTS streams. We analyzed the features of 44 standard files recorded using all recording options of seven cameras. We checked whether integrity can be validated on unmanipulated videos recorded in various environments. In addition, we considered whether manipulated MTS files edited in video editing software could be validated. Experimental results show that all unmanipulated and manipulated MTS files with known recording devices were discriminated only when all five features were checked. These results show that the proposed method verifies the integrity of MTS files, strengthening the validity of MTS file-based evidence in trials.

Clean mucosal area detection of gastroenterologists versus artificial intelligence in small bowel capsule endoscopy.

Studies comparing the detection of clean mucosal areas in capsule endoscopy (CE) using human judgment versus artificial intelligence (AI) are rare. This study statistically analyzed gastroenterologist judgments and AI results. Three hundred CE video clips (100 patients) were prepared. Five gastroenterologists classified the video clips into 3 groups (≥75% [high], 50%-75% [middle], and < 50% [low]) according to their subjective judgment of cleanliness. Visualization scores were calculated using an AI algorithm based on the predicted visible area, and the 5 gastroenterologists' judgments and AI results were compared. The 5 gastroenterologists evaluated CE clip video quality as "high" in 10.7% to 36.7% and as "low" in 28.7% to 60.3% and 29.7% of cases, respectively. The AI evaluated CE clip video quality as "high" in 27.7% and as "low" in 29.7% of cases. Repeated-measures analysis of variance (ANOVA) revealed significant differences in the 6 evaluation indicators (5 gastroenterologists and 1 AI) (P < .001). Among the 300 judgments, 90 (30%) were consistent with 5 gastroenterologists' judgments, and 82 (91.1%) agreed with the AI judgments. The "high" and "low" judgments of the gastroenterologists and AI agreed in 95.0% and 94.9% of cases, respectively. Bonferroni's multiple comparison test showed no significant difference between 3 gastroenterologists and AI (P = .0961, P = 1.0000, and P = .0676, respectively) but a significant difference between the other 2 with AI (P < .0001). When evaluating CE images for cleanliness, the judgments of 5 gastroenterologists were relatively diverse. The AI produced a relatively universal judgment that was consistent with the gastroenterologists' judgements.

EasyFlyTracker: A Simple Video Tracking Python Package for Analyzing Adult Drosophila Locomotor and Sleep Activity to Facilitate Revealing the Effect of Psychiatric Drugs.

The mechanism of psychiatric drugs (stimulant and non-stimulant) is still unclear. Precision medication of psychiatric disorders faces challenges in pharmacogenetics and pharmacodynamics research due to difficulties in recruiting human subjects because of possibility of substance abuse and relatively small sample sizes. Drosophila is a powerful animal model for large-scale studies of drug effects based on the precise quantification of behavior. However, a user-friendly system for high-throughput simultaneous tracking and analysis of drug-treated individual adult flies is still lacking. It is critical to quickly setup a working environment including both the hardware and software at a reasonable cost. Thus, we have developed EasyFlyTracker, an open-source Python package that can track single fruit fly in each arena and analyze Drosophila locomotor and sleep activity based on video recording to facilitate revealing the psychiatric drug effects. The current version does not support multiple fruit fly tracking. Compared with existing software, EasyFlyTracker has the advantages of low cost, easy setup and scaling, rich statistics of movement trajectories, and compatibility with different video recording systems. Also, it accepts multiple video formats such as common MP4 and AVI formats. EasyFlyTracker provides a cross-platform and user-friendly interface combining command line and graphic configurations, which allows users to intuitively understand the process of tracking and downstream analyses and automatically generates multiple files, especially plots. Users can install EasyFlyTracker, go through tutorials, and give feedback on http://easyflytracker.cibr.ac.cn. Moreover, we tested EasyFlyTracker in a study of Drosophila melanogaster on the hyperactivity-like behavior effects of two psychiatric drugs, methylphenidate and atomoxetine, which are two commonly used drugs treating attention-deficit/hyperactivity disorder (ADHD) in human. This software has the potential to accelerate basic research on drug effect studies with fruit flies.

Detection and Tracking of a Moving Object Using Canny Edge and Optical Flow Techniques

Aims: In the discipline of computer vision, detecting and tracking moving objects in a succession of video frames is a critical process. Image noise, complicated object motion and forms, and video real-time processing are some of the challenges faced by existing methods. Hence, they are computationally complex and susceptible to noise. This work utilized Canny Edge and Optical Flow (CE-OF) techniques for identifying and tracking moving objects in video files.&#x0D; Methodology: Video sequence datasets in Avi and Mp4 format from MathWorks and YouTube were used to evaluate the developed CE-OF technique. The video clip's frames were sampled several times and the frame rate display was calculated. The original images were converted to grayscale, preprocessed, and CE-OP was applied to identify and track the moving object. The results of the CE-OF and optical flow techniques in terms of accuracy, precision, false acceptance rate, false rejection rate, and processing time were obtained and compared. The performance of the developed technique was evaluated using accuracy, precision, false acceptance rate (FAR), false rejection rate (FRR) and processing time. The results obtained were 94.12%, 92.86%, 25.00%, 25.00%, and 19.51s for Mp4; and 93.33%, 90.91%, 20.00%, 20.00%, and 44.11s for Avi video 1 format, respectively.&#x0D; Conclusion: The developed CE-OF is a better competition in terms of accuracy and time compared with well-known techniques in the literature. The CE-OF technique performed better compared with the conventional methods in detecting and tracking a moving object. Therefore, it can be adopted in the designing of intelligent surveillance systems.

Automatic reconstruction of deleted AVI video files composed of scattered and corrupted fragments

Video files of surveillance cameras frequently play a role of major evidence for criminals or accidents. But, if the video file containing the evidence is deleted, we need to recover it if possible. In this paper, we propose a recovery scheme for deleted video files with AVI format on FAT32 file system. The proposed scheme first recovers deleted video files from unallocated storage space exploiting both signatures of video frames and behaviours of file systems. The scheme finds fragments of deleted video files based on the start indicator of video frames or the file header signature, and connects the found fragments based on the file allocation patterns of FAT32 file system. Next, if a recovered video file is partially corrupted, the scheme automatically reconstructs the corrupted AVI video file so that the video file can be played back. The lost file header of the corrupted video file is reconstructed based on the file header of a reference video file, and the lost data multimedia data is filled with zero. Through practical implementation, we show that the proposed scheme recovers deleted video files from unallocated storage space and reconstructs corrupted AVI video files.

Seleksi Wajah Digital Menggunakan Algoritma Camshift

Real time for digital face database selection using camshift algorithm] Education taken 4-5 years affects physical development. This study uses student digital video data. The recording results are used to identify certain characteristics possessed by a student later stored in the digital file database catalog. The stages of the study consisted of identification, recognition and matching of faces. It starts from converting .mp4 videos to .AVI format. The CAMShift algorithm uses basic HSV colors for tracking face position (tracking) and faces recognition. 1-2 seconds video produces 45-200 frames PNG file. The face matching test results were carried out on several video play, the success of detection: 100% selected, 45%-60%, 80-90%, concluded around 50%-100% successful. Face movements will be caught by the centroid bounding box, if the color of the face is dominant in Hue.

Face Recognition System for Indoor Applications Based on Video with the LNMF and NMFsc Methods

Face detection and face recognition are among the most important research topics in computer vision, as many applications use faces as objects of biometric technology. One of the main issues in applying face recognition is recording the attendance of active participants in a room. The challenge is that recognition through video with multiple object conditions in one frame may be difficult to perform. The Principal Component Analysis method is commonly used in face detection. Principal Component Analysis still has shortcomings: the accuracy decreases when it is applied to large datasets and performs slowly in real-time applications. Therefore, this study simulates a face recognition system installed in a room based on video recordings using Non-negative Matrix Factorization suppressed carrier and Local Non-negative Matrix Factorization methods. Data acquisition is obtained by capturing video in classrooms with a resolution of 640 x 480 pixels in RGB, .avi format, video frame rate of 30 fps, and video duration of ±10 seconds. The proposed system can perform face recognition in which the average accuracy value of the Local Non-negative Matrix Factorization method is 71.61% with a computation time of 152,634 seconds. By contrast, the average accuracy value of the Non-negative Matrix Factorization suppressed carrier method is 86.76% with a computation time of 467,785 seconds. The proposed system is expected to be used for simultaneously finding and identifying faces in real time.

Encryption Video Using NTRU and Chaotic Algorithms

The rapid development of most multimedia technologies led to the creation and transmission of much of this type of data in various fields, including medical, military and commercial, which contain sensitive information that can only be accessed by the competent authorities. Because of this, privacy has become vital. Many encryption algorithms have been used to provide security for video transmission. In this paper, NTRU and chaotic algorithms are used for video encryption, which includes sensitive information. The system is designed to encode AVI, WMV, MOV, MP4 and other video file formats. This type of video is encrypted using the NTRU algorithm and decrypted using chaotic algorithm to ensure a high level of strength and security, thus speeding up the encryption process and returning the video to its original location without losing any data. Visual Basic .net 2015 was used to implement this system.

DETEKSI KEDIPAN MATA PADA VIDEO MENGGUNAKAN OPEN CV

In the development of technology in the current era is one of the most rapid progress, it is marked by almost all managers of data and information has been done with the computer because of the increasingly diverse information issues handled, Detection of objects is one of the most important early stages before Done object recognition process. Eye blink detection can be used to open a new file or an application. In this research use case detection eye blinking on video using OpenCV to open notepad application. The blink detection uses the haar cascade classifier method for realtime detection and the OpenCV Library. The first step determines the pattern 1111100000. Next enter the video sample avi format to match with a predetermined pattern. In this program the system managed to detect the eye according to the pattern by circling the eye area when the eyes are open or literate and when the eyes closed or brake there is no circle in the eye area for the correct video sample.

Evaluation of a Methodology for Automated Cell Counting for Streak Mode Imaging Flow Cytometry

Identification of Circulating Tumor Cells (CTCs) has shown promising clinical applications, but since CTCs are found in very low concentration in blood large sample volumes are needed for meaningful enumeration. This issue impedes the analysis of CTCs using standard flow cytometry due to its low throughput. To address this issue, a high throughput microfluidic cytometer was recently developed using a wide field flow- flow cell instead of the conventional narrow hydrodynamic focusing cells (used in traditional flow cytometry) enabling analysis of large volumes at lower flow rate. This wide-field flow cytometer adopts a technique known as “streak photography” where exposure times and flow velocities are set such that the particles are imaged as short “streaks”. Since streaks are imaged with large number of pixels, they are easily distinguished from the noise which appears as “speckles” increasing the detection capabilities of the device, making it more suitable for analysis using current low sensitivity, high noise webcams or mobile phone cameras. The non-stationary nature of the high noisy background found in streak cytometry introduces additional challenges for automated cell counting methods using traditional cell detection techniques such TLC, CellProfiler, CellTracker and other tools based in traditional edge detection (e.g., Canny based filters) or manual thresholding. In order to address this issue, we developed a new automated enumeration approach that does not rely on edge detection or manual thresholding of individual cells, rather is based in image quantizing, morphological operations, 2D order-statistic filtering and decisions rules that take into account knowledge of the structure and expected location of the streaks in consecutive frames. We evaluated our approach comparing it with two current methods representing the major computational modalities for cell detection: CellTrack (based in edge detection) and MTrack2 (based in manual thresholding). Samples of 1 cell/mL nominal concentration were analyzed in batch size of 30 mL at flow rate of 10 mL/min and imaged at 4 frames per second (fps), the files were saved in uncompressed AVI format files. The cells were annotated and the signal to noise ratio (SNR) was calculated. For samples with average SNR greater than 4.4 dB, our method achieved a sensitivity of 91% compared to CellTrack (60%) and MTrack2 (71%). The True Positive Rate (TPR) of cells detected was 0.93 for our method compared with 0.80 for Mtrack2 and 0.29 for CellTrack. This demonstrated the ability of the algorithm to count rare cells with high accuracy for concentrations of 1 cell/mL with SNR greater than 4.4 dB. This cell counting capability will enable to automate low cost imaging flow cytometry based on CCD detector and the expansion of cell-based clinical diagnostics in resource-poor settings.

Cascaded Fresnel holographic image encryption scheme based on a constrained optimization algorithm and Henon map

We propose an image encryption scheme using chaotic phase masks and cascaded Fresnel transform holography based on a constrained optimization algorithm. In the proposed encryption scheme, the chaotic phase masks are generated by Henon map, and the initial conditions and parameters of Henon map serve as the main secret keys during the encryption and decryption process. With the help of multiple chaotic phase masks, the original image can be encrypted into the form of a hologram. The constrained optimization algorithm makes it possible to retrieve the original image from only single frame hologram. The use of chaotic phase masks makes the key management and transmission become very convenient. In addition, the geometric parameters of optical system serve as the additional keys, which can improve the security level of the proposed scheme. Comprehensive security analysis performed on the proposed encryption scheme demonstrates that the scheme has high resistance against various potential attacks. Moreover, the proposed encryption scheme can be used to encrypt video information. And simulations performed on a video in AVI format have also verified the feasibility of the scheme for video encryption.

An Efficient and Robust High Efficiency Video Coding Framework to Enhance Perceptual Quality of Real-Time Video Frames

Different level of compression on real-time video streaming has successfully reduced the storage space complexities and bandwidth constraints in the recent times. This paper aims to design and develop a novel concept towards the enhancement of perceptual quality of a real-time video frames. The proposed model has been experimented considering multi-level compression operation using H.265 where .avi moving frames standards play a crucial role. The study also applies a novel concept of High-efficiency video coding (HEVC) for adaptive live video streaming over a mobile network. The proposed study aims to formulate a multi-level optimization for HEVC to enhance the performance of both encoding and decoding mechanisms at the client as well as server side to ensure higher compression rate. The experimental outcomes also show that the proposed protocol achieves better performance ratio and overall; throughput in comparison with conventional H.263, H.264 by enhancing the perceptual quality of .avi format real-time video frames.

Innovative methods for knowledge transfer

At this time, learning takes place, either with classic books on paper support or using books scanned or drawn and further converted into PDF or PPT files that are printed on type support CD / DVD. The latter modern means of learning, the study adds live on the Internet using search engines and not least e-learning method, which allows the study of bibliographic related materials in PDF or PPT, stacked and grouped on the basis of a curriculum imposed which can be accessed on a website via a user name and password. Innovative methods come to successfully use other file types than those mentioned above. The graphics in teaching technical subjects such as descriptive geometry can be achieved using animated PowerPoint files, allowing for visualization of steps to be taken, in the case of solving by drawing a descriptive geometry. Another innovative method relies on the use of HTML files, inspired by related sites help design software packages that can be used when teaching descriptive geometry that the technical design. Through this work, the author has proposed to present a new innovative method, which is inspired by the methods listed above, but involves using AVI files to teaching of computer-assisted type graphics or info graphics. In general this new author's method lends itself particularly well to the teaching of the use of software packages because the student actually see the place from where the delivered command is accessed and contextual options of right button of the mouse. These laboratory courses or mentoring can be freestanding cards support CD / DVD or can be posted on websites with restricted access based on user name and password. Practically paper presents the methodology of creating courses and tutorials in AVI format, and how to monitor the degree of accessing the website, on which there were posted mentioned teaching materials, using the tools offered by Google Analytics. The results consist of graphical work, about the degree of access to educational materials, made on the basis of various criteria, such as the: time of access, access location, age of those who accessed, chapters accessed, etc. Finally the author presents his findings on the benefits of this method.

Multi-object extraction from topview group-housed pig images based on adaptive partitioning and multilevel thresholding segmentation

The aim of this study is to provide a feasible method that can accurately extract individual pigs from a drinker and feeder zone; therefore, an object extraction method based on adaptive partitioning and multilevel thresholding segmentation is proposed. First, a single frame image is enhanced using histogram equalisation, and then it is segmented with a maximum entropy global threshold. The initial segmentation objects are obtained by extracting a “valid area” and morphological processing. Then, each object centroid is calculated from the initially segmented objects, and the original image is adaptively divided into multiple circular sub-blocks whose origin is the centroid and radius is the maximum distance from the centroid to the edge point. Finally, an accurate secondary segmentation result is obtained using multilevel thresholding segmentation in each sub-block. The test data included thirty random videos collected in AVI format, and 9000 frames from 5 days × 6 videos × 120 s × 25 frames s−1 were selected. Results show that the average detection rate is 92.5%. This paper also analyses the possible applications of the proposed method to pig behaviour analysis, individual recognition, and weight estimation.

Brazilian vehicle identification using a new embedded plate recognition system

Expert systems for parking lot access control are developed in vehicle management through tracking and number recognition. These systems commonly use cameras to identify a vehicle through its license plates based on intelligent and optical character recognition techniques. This paper presents a new system to detect and recognize Brazilian vehicle license plates, in which the registered users have permission to enter the location. For this, techniques of Digital Image Processing were used, such as Hough Transform, Morphology, Threshold and Canny Edge Detector to extract characters, as well as Least Squares, Least Mean Squares, Extreme Learning Machine, and Neural Network Multilayer Perceptron to identify the numbers and letters. The system was tested with 700 videos with a resolution of 640×480 pixels and AVI format, granting access only when the plate was registered, getting a 98.5% success rate on the tested cases. The movement detection step is linked to the system, becoming faster and more accurate in real time. Thus, can be concluded that the proposed system is a promising tool with high potential which can be applied commercially.

24 bit renkli hareketli resimler (video) üzerinde geliştirilen sırörtme yöntemi

Techniques for information hiding ( Steganography) have nowadays become increasingly more sophisticated and widespread. Communication channels have insecure. So problems of security have become. Kriptography and Steganography have devised a technology for needs of data security. Kriptography has curious about data security, Steganography has curious about data security of communication. In this study. the encrypted message that is on .AVI format very different from the classical LSB data embedding technique based data embedding algorithm is mainly used as RGB. This coding technique has increased considerably as the relative capacity of data embedding.

Image/video encryption using single shot digital holography

We propose a method for image/video encryption that combines double random-phase encoding in the Fresnel domain with a single shot digital holography. In this method, a complex object field can be reconstructed with only single frame hologram based on a constrained optimization method. The system without multiple shots and Fourier lens is simple, and allows to dynamically encrypt information. We test the proposed method on a computer simulated image, a grayscale image and a video in AVI format. Also we investigate the quality of the decryption process and the performance against noise attacks. The experimental results demonstrate the performance of the method.

The ways of streamlining digital image processing algorithms used for detection of lines in transport scenes video recording

The paper is focused on describing the use of digital image processing methods, with emphasis on application in road transport, which warns the driver in case of unintentional lane departure. The problem of detecting lines is extensive and consists of a series of problems which partial results were published in other articles. The authors analyse the possible solutions to find the horizontal traffic signs using segmentation methods designed for finding lines in each video frame of the captured traffic scene on the highway. To speed up the process and reduce the volume of processed data it was necessary to find ways of improving the effectiveness of the line detection algorithm. These methods are described in the present paper. In the section describing the practical implementation we have shown the way of finding road markings using Sobel edge detector algorithm and modified Hough transform in the image data recorded in .AVI format file and from the position of the vehicle and lane found position to detect the crossing of lane.

Biomechanical Characteristics of Movement Phases of Clean & Jerk Style in Weightlifting Performance

The purpose of this paper is to highlight the kinematic and dynamic characteristics of movement phases of Clean & Jerk style in weightlifting performance. This scientific approach has led to a study conducted during the European Junior Weightlifting Championships, Bucharest, 2011, on a group of 7 athletes, finalists of 56kg class. The methodology of research focused on video recording, conversion of video capture into AVI format and the video biomechanical analysis of weightlifters’ performances by means of a specialized program named Physics ToolKit. Bottom of FormEach execution has shown the trajectories of the main joints involved in movement, highlighting the kinematic and dynamic characteristics of Clean & Jerk style phases. The comparative analysis of the biomechanical indicators of movement phases in terms of start, barbell drive to jerk, the jerk, getting under barbell, lifting from the rack, barbell catch over the head highlights the duration of phases, the execution speed and the force to overcome the resistance of the barbell. The study results revealed the kinematic and dynamic characteristics of movement phases of the Clean & Jerk style, especially the jerk, phases that had an influence on the performances achieved in competition.

Windows Azure 기반의 N-스크린 서비스를 위한 실시간 동영상 재생 기법

본 논문에서는 Windows Azure 기반의 N-스크린 서비스를 위한 실시간 동영상 재생 기법을 제안한다. 이 기법은 각 노드의 성능에 따라 원본 동영상을 차등 분할하여 재생 블록을 생성한다. 그리고 차등 분할한 재생 블록을 해당 노드에 할당하여 트랜스 코딩함으로써 트랜스 코딩 소요시간을 줄인다. 본 논문에서는 시뮬레이션을 통하여 제안한 동영상 재생기법이 기존의 기법에 비해 N-스크린 서비스를 위한 실시간 동영상재생에 효과적임을 보인다. 시뮬레이션에서는 상용화된 클라우드 시스템인 Windows Azure 기반에서 AVI 포맷 300MB 원본 동영상을 각 노드의 성능에 따라 차등 분할한다. 그리고 Windows Azure의 이기종 노드에 분산 할당하여 mp4와 Flv 포맷으로 트랜스 코딩하면서 트랜스 코딩 소요시간을 측정한다. 그 결과 본 논문의 제안 기법이 기존의 균등 분할 기법에 비해 Windows Azure 기반의 N-스크린 서비스의 성능을 향상시킨다. In this paper, we propose a real-time video playback scheme for the N-Screen service based on Windows Azure. This scheme creates several playback blocks based on the performance of each node by non-uniform splitting of the original video. To reduce transcoding-time, it allocates the playback blocks to a corresponding node by transcoding the playback blocks. Through the simulation, we show that it is more effective to use real-time video playback for the N-screen service than the previous method. The proposed scheme splits an AVI format 300MB source video with non-uniform playback blocks. It allocates the playback blocks to the heterogeneous node of Windows Azure, the commercial cloud system and measures of transcoding-time by transcoding non-uniform playback blocks to mp4 and Flv format. As a result, the proposed scheme improves the performance of the N-screen service based on Windows Azure compared to the previous uniform split strategy.