Performance Evaluation of Digital Image Processing by Using Scilab

Scilab is an open-source, cross-platform computational environment software available for academic and research purposes as a free of charge alternative to the matured computational copyrighted software such as MATLAB. One of important library available for Scilab is image processing toolbox dedicated solely for image and video processing. There are three major toolboxes for this purpose: Scilab image processing toolbox (SIP), Scilab image and video processing toolbox (SIVP) and recently image processing design toolbox (IPD). The target discussion in this paper is SIVP due to its vast use out there and its capability to handle streaming video file as well (note that IPD also supports video processing). Highlight on the difference between SIVP and IPD will also be discussed. From testing, it is found that in term of looping test, Octave and FreeMat are faster than Scilab. However, when converting RGB image to grayscale image, Scilab outperform Octave and FreeMat.

Use of videos for teaching a foreign language to cadets of higher military educational institutions and servicemen

The relevance of the research is conditioned by the necessity to acquire knowledge of a foreign language by cadets of higher military educational institutions and servicemen for successful performance of official duties. In the article, the scientific and methodological literature on the use of video materials for teaching a foreign language has been analyzed. The aim of the article was to define the importance and necessity of using video materials for teaching English to cadets of higher military educational institutions and servicemen. The requirements of English knowledge in listening and speaking for servicemen, whose knowledge of English corresponds to the standardized speech level ‘functional’, have been considered. It has been found that servicemen have to understand conversations on both everyday and professional topics and to be able to communicate effectively in everyday and standard working situations. Based on the analysis of the literature, the advantages of the use of video materials for teaching a foreign language have been determined; the main techniques of using video materials (watching video materials without sound, listening to the plot without watching a video file, watching a video file with stops, partial watching (when a part of the screen is closed and cadets / servicemen have to guess what was closed), division of cadets into two groups) and requirements for selecting video files have been characterized. In the article, the necessity to teach to understand the real speech of native speakers has been highlighted; the description of oral informal spontaneous speech has been given; the practice of selective ignoring the heard information has been clarified. The examples of websites, which correspond to topics of teaching of cadets / servicemen have been given (U.S. Army Talent Management, VSB Defense, Military Comparisons, Defense Forces and Military Center). Taking into account the received information, the recommendations on the work with video materials have been given. The necessity of teaching cadets / servicemen how to work with video materials and how to develop the ability to learn English independently with the help of video materials was specified.

ACCV: automatic classification algorithm of cataract video based on deep learning

Purpose A real-time automatic cataract-grading algorithm based on cataract video is proposed. Materials and methods In this retrospective study, we set the video of the eye lens section as the research target. A method is proposed to use YOLOv3 to assist in positioning, to automatically identify the position of the lens and classify the cataract after color space conversion. The data set is a cataract video file of 38 people's 76 eyes collected by a slit lamp. Data were collected using five random manner, the method aims to reduce the influence on the collection algorithm accuracy. The video length is within 10 s, and the classified picture data are extracted from the video file. A total of 1520 images are extracted from the image data set, and the data set is divided into training set, validation set and test set according to the ratio of 7:2:1. Results We verified it on the 76-segment clinical data test set and achieved the accuracy of 0.9400, with the AUC of 0.9880, and the F1 of 0.9388. In addition, because of the color space recognition method, the detection per frame can be completed within 29 microseconds and thus the detection efficiency has been improved significantly. Conclusion With the efficiency and effectiveness of this algorithm, the lens scan video is used as the research object, which improves the accuracy of the screening. It is closer to the actual cataract diagnosis and treatment process, and can effectively improve the cataract inspection ability of non-ophthalmologists. For cataract screening in poor areas, the accessibility of ophthalmology medical care is also increased.

Real Time Implementation of Video Compression Based on DWT

In this paper highly efficient 3D Discrete Wavelet Transform architecture is designed and implemented on seven series FPGA. The throughput is analyzed and its performance matrices are compared with different video file format. Today top of the line high-end image and video consume huge amount of memory. The designed architecture of DWT based video compression is again executed in parallel processing mode and its execution time is tabulated demonstrates reduced the processing or execution time. This paper demonstrates the superiority of the designed architecture both in normal mode of execution and parallel processing mode of execution .We know that higher the throughput of the video processing design results in Low power consumption. The Internal Architecture of the design is explained in brief and is synthesized in Xilinx Vivado 17.4 and implemented on Zed board. Based on the experimental results of the design being implemented on FPGA, demonstrates the memory saving capabilities and superiority of this architecture. The resultant architecture has drastically reduced latency and has enhanced the speed of operation.

Developing and conducting classes using video tutorials

This article discusses the issues of developing and conducting lessons using the method of video lessons. The stages of organizing video lessons during the distance learning are provided.The article discusses the video lesson itself in different ways, for example, the following three types of lessons can be distinguished:a lesson on the introduction (explanation) of new material; lessons on consolidation of knowledge, skills and abilities are provided; summarizes knowledge, skills and abilities and ends with a control lesson.Topical issues are addressed in order to create short videos on each topic so that students can review the material on their own and not wait for the teacher’s answer. There are several programs for creating video lessons. They are: Сamtasia Studio, Macromedia Flash, Screen2exe, Jing, Werbineria, Wink.It is shown that the whole process can be divided into three stages: write a video tutorial on Camtasia Recorder, editing (post-editing) is provided in the Camtasia Studio editor,the video file is encoded.

Efficient Algorithms for E-Healthcare to Solve Multiobject Fuse Detection Problem

Object detection plays a vital role in the fields of computer vision, machine learning, and artificial intelligence applications (such as FUSE-AI (E-healthcare MRI scan), face detection, people counting, and vehicle detection) to identify good and defective food products. In the field of artificial intelligence, target detection has been at its peak, but when it comes to detecting multiple targets in a single image or video file, there are indeed challenges. This article focuses on the improved K-nearest neighbor (MK-NN) algorithm for electronic medical care to realize intelligent medical services and applications. We introduced modifications to improve the efficiency of MK-NN, and a comparative analysis was performed to determine the best fuse target detection algorithm based on robustness, accuracy, and computational time. The comparative analysis is performed using four algorithms, namely, MK-NN, traditional K-NN, convolutional neural network, and backpropagation. Experimental results show that the improved K-NN algorithm is the best model in terms of robustness, accuracy, and computational time.

A Graphical Based Video Steganography

In today’s digital media data communication over the internet increasing day by day. Therefore the data security becomes the most important issue over the internet. With the increase of data transmission, the number of intruders also increases. That’s the reason it is needed to transmit the data over the internet very securely. Steganography is a popular method in this field. This method hides the secret data with a cover medium in a way so that the intruders cannot predict the existence of the data. Here a steganography method is proposed which uses a video file as a cover medium. This method has five main steps. First, convert the video file into video frames. Then a particular frame is selected for embedded the secret data. Second, the Least Significant Bit (LSB) Coding technique is used with the double key security technique. Third, an 8 characters password verification process. Fourth, reverse the encrypted video. Fifth, signature verification process to verify the encryption and decryption process. These five steps are followed by both the encrypting and decrypting processes.

Realising a Push Button Modality for Video-Based Forensics

Complexity and sophistication among multimedia-based tools have made it easy for perpetrators to conduct digital crimes such as counterfeiting, modification, and alteration without being detected. It may not be easy to verify the integrity of video content that, for example, has been manipulated digitally. To address this perennial investigative challenge, this paper proposes the integration of a forensically sound push button forensic modality (PBFM) model for the investigation of the MP4 video file format as a step towards automated video forensic investigation. An open-source multimedia forensic tool was developed based on the proposed PBFM model. A comprehensive evaluation of the efficiency of the tool against file alteration showed that the tool was capable of identifying falsified files, which satisfied the underlying assertion of the PBFM model. Furthermore, the outcome can be used as a complementary process for enhancing the evidence admissibility of MP4 video for forensic investigation.

Grayscale Drone Inspection Image Enhancement Framework for Advanced Bridge Defect Measurement

This paper presents a framework to better identify and measure defects in a bridge using drone-based inspection images integrated with grayscale image enhancement techniques. For this study, a DJI Matrice 210 drone was used for the inspection of a three-span timber bridge with concrete decking located in Keystone, South Dakota. During the inspection, the drone recorded a series of videos of the bridge using the MOVie (MOV, video file extension) video format. MOV-based image analysis was conducted to identify a variety of defect types (i.e., efflorescence, water leakage, spalling, and discoloration) on the bridge. For improvement of defect visibility, the grayscale image enhancement technique was applied to determine visually enhanced images for the individual defect. The technique used grayscale image histogram processing that can adjust images using realignment of contrast histograms, in which contrasts of each pixel of the grayscale images have their own number from 0 for black to 255 for white in the image. With the enhanced images, pixel-based measurement was conducted to quantify the defects, including efflorescence (3.75 m2), water leakage (4.21 m2), spalling (0.74 m2), and discoloration (2.12 m2). Based on these findings, the grayscale drone inspection image enhancement technique enabled the demonstration of defect visibility adjustment and improvement for more reliable identification and measurement of the defects in the bridge.