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Network Vulnerability Analysis on Brain Signal/image Databases Using Nmap and Wireshark Tools

IEEE ACCESS 2018年 6卷 57144-57151页

作者： Bagyalakshmi, G. Rajkumar, G. Arunkumar, N. Easwaran, M. Narasimhan, K. Elamaran, V Solarte, Mario Hernandez, Ivan Ramirez-Gonzalez, Gustavo SASTRA Deemed Univ Sch EEE Thanjavur 613401 India Univ Cauca Telemat Dept Popayan 190001 Colombia

Brain signal processing is important for not only the physiologist doing analysis investigation, but also for the clinician inspecting patients, biomedical engineer who is responsible for collecting, processing, and interpreting the electroencephalogram signals by modeling systems and algorithms for their manipulations. The abundant materials on the subject of brain signal/image processing are scattered in different scientific, technological and physiological journals, international conference proceedings, and also in various databases. Therefore, it is altogether a difficult, too time-consuming, and much tiresome work, exclusively to the newcomers in this field. Therefore, this paper focuses on providing the list of popular databases available belonging to the neurological signals, brain signal/image collections, and so on. The count and the kinds of attacks across the networked computer systems have hiked the significance of computer network security. At present, network administrators use to inspect, examine, scrutinize, review, and analyze the network traffic to figure out what is going on and to set up a prompt response in the event of an identified attack. This paper analyzes the different sweep techniques such as Ping sweep, TCP sweep, and Null sweep on the popular databases about the brain signal/image collections. The results of the Ping sweep support status, TCP sweep times, and Null scan times on different servers are discussed finally.

关键词： Brain signal/image Null scan packet sniffer Ping sweep TCP sweep Wireshark

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image reconstruction using the modified texture synthesis algorithm

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IOP conference Series: Materials Science and Engineering 2021年第1期1029卷

作者： R R Ibadov N V Gapon S R Ibadov S V Kucheryavenko Southern Federal University Taganrog Russia Lab. 'Mathematical methods of image processing and intelligent computer vision systems' Don State Technical University Rostov-on-Don Russia

The article discusses a method for image reconstruction based on the search for similar blocks using a texture synthesis algorithm. The effectiveness of the new approach is shown using several examples for various areas with lost pixels. The subject of the research is methods and algorithms for processing space-time reconstruction of two-dimensional signals based on a geometric model of images. The object of research is a set of test static images. The result of the study is a modification of the image reconstruction method based on the search for similar blocks in order to reduce the error in image reconstruction. The novelty of the work is an algorithm that improves the quality of image restoration. The results obtained make it possible to reduce the root mean square error.

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Real-time Head Detection for Automated Passenger Counting in Embedded systems 3

Real-time Head Detection for Automated Passenger Counting in...

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3rd International Symposium on Computer Science and Intelligent Control, ISCSIC 2019

作者： Kim, Hyunduk Lee, Sang-Heon Sohn, Myoung-Kyu Convergence Research Center for Future Automotive Technology DGIST Daegu Korea Republic of

ISBN: (纸本)9781450376617

Head detection is a key problem for automated passenger counting systems. In recent decades, considerable effort has been expended to develop an accurate and reliable head detector. However, head detection is still a challenging task because of problems caused by variations in pose and occlusions. Recently, general object detection algorithms based on convolutional neural networks (CNNs), such as Faster R-CNN, SSD and YOLO, have been successful. However, these algorithms require the use of a Graphics processing Unit (GPU) for real-time performance. In this study, we focused on developing real-time head detection in an embedded system. Starting with the Tiny-YOLOv3 network, we applied the following strategies to achieve real-time performance in a non-GPU environment. First, we reduced the input image size to 224x224. Second, we added an extra yolo layer to detect smaller heads. Third, we removed batch normalization. Finally, we conducted depthwise separable convolution rather than traditional convolution. Three public datasets, HollywoodHeads, SCUT-HEAD, and CrowdHuman, were exploited to train and test the proposed network, and Average Precision (AP) at Intersection over Unit (IoU) = 0.5 were used to evaluate the tests. Experimental results showed that the proposed network perform better and faster than Tiny-YOLOv3. © 2019 ACM.

关键词： Embedded systems

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Improving traffic light recognition methods using shifting time-windows 25

Improving traffic light recognition methods using shifting t...

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25th International conference on systems, Signals and image processing (IWSSIP)

作者： Blokus, Adam Krawczyk, Henryk Gdansk Univ Technol Fac Elect Telecommun & Informat Gdansk Poland

ISBN: (纸本)9781538669792

We propose a novel method of improving algorithms recognizing traffic lights in video sequences. Our focus is on algorithms for applications which notify the driver of a light in sight. Many existing methods process images in the recording separately. Our method bases on the observation that real-life videos depict underlying continuous processes. We named our method FSA (Frame Sequence Analyzed). It is applicable for any underlying algorithm and improves it by adding an additional result post-processing step. Our experiments are based on improving a published real-time traffic light recognition algorithm. Its general description has been provided by its authors, which allowed us to create a best-effort implementation for testing. We verify the effectiveness of the FSA method on a public dataset, acquiring very good results - improving the underlying algorithm in terms of all considered error measures. In the end, conclusions and possible future improvements are discussed.

关键词： image classification traffic light recognition video classification FSA method shifting window

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SCFusion: Real-time Incremental Scene Reconstruction with Semantic Completion

SCFusion: Real-time Incremental Scene Reconstruction with Se...

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International conference on 3D Imaging, Modeling, processing, visualization and Transmission (3DIMPVT)

作者： Shun-Cheng Wu Keisuke Tateno Nassir Navab Federico Tombari Technische Universitat München Germany Google Inc. Switzerland

ISBN: (数字)9781728181288

ISBN: (纸本)9781728181295

Real-time scene reconstruction from depth data inevitably suffers from occlusion, thus leading to incomplete 3D models. Partial reconstructions, in turn, limit the performance of algorithms that leverage them for applications in the context of, e.g., augmented reality, robotic navigation, and 3D mapping. Most methods address this issue by predicting the missing geometry as an offline optimization, thus being incompatible with real-time applications. We propose a framework that ameliorates this issue by performing scene reconstruction and semantic scene completion jointly in an incremental and real-time manner, based on an input sequence of depth maps. Our framework relies on a novel neural architecture designed to process occupancy maps and leverages voxel states to accurately and efficiently fuse semantic completion with the 3D global model. We evaluate the proposed approach quantitatively and qualitatively, demonstrating that our method can obtain accurate 3D semantic scene completion in real-time.

关键词： Three-dimensional displays Semantics image reconstruction Real-time systems Pipelines Shape Solid modeling

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A Survey of Computer vision Based Corrosion Detection Approaches 2nd

A Survey of Computer Vision Based Corrosion Detection Approa...

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2nd International conference on Information and Communication Technology for Intelligent systems (ICTIS)

作者： Ahuja, Sanjay Kumar Shukla, Manoj Kumar Amity Univ AIIT Noida Uttar Pradesh India Amity Univ ASET Noida Uttar Pradesh India

ISBN: (纸本)9783319636450;9783319636443

There are various destructive as well as non-destructive techniques available to detect corrosion in metallic surfaces. Digital image processing is widely being used for the corrosion detection in metallic surface. This non-destructive approach provides cost effective, fast and reasonably accurate results. Several algorithms have been developed by different researchers and research groups for detecting corrosion using digital image processing techniques. Several algorithms related to color, texture, noise, clustering, segmentation, image enhancement, wavelet transformation etc. have been used in different combinations for corrosion detection and analysis. This paper reviews the different image processing techniques and the algorithms developed and used by researchers in various industrial applications.

关键词： Computer vision image processing Corrosion detection

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Region Based Approach for Binarization of Degraded Document images 21st

Region Based Approach for Binarization of Degraded Document ...

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21st International Multi-conference on Advanced Computer systems, ACS 2018

作者： Michalak, Hubert Okarma, Krzysztof Department of Signal Processing and Multimedia Engineering Faculty of Electrical Engineering West Pomeranian University of Technology Szczecin 26 Kwietnia 10 Szczecin71-126 Poland

ISBN: (纸本)9783030033132

Binarization of highly degraded document images is one of the key steps of image preprocessing, influencing the final results of further text recognition and document analysis. As the contaminations visible on such documents are usually local, the most popular fast global thresholding methods should not be directly applied for such images. On the other hand, the application of some typical adaptive methods based on the analysis of the neighbourhood of each pixel of the images is time consuming and not always leads to satisfactory results. To bridge the gap between those two approaches the application of region based modifications of some histogram based thresholding methods has been proposed in the paper. It has been verified for well known Otsu, Rosin and Kapur algorithms using the challenging images from Bickley Diary dataset. Experimental results obtained for region based Otsu and Kapur methods are superior in comparison to the use of global methods and may be the basis for further research towards combined region based binarization of degraded document images. © 2019, Springer Nature Switzerland AG.

关键词： Character recognition

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Gray Scale image Restoration Using Advanced Atmospheric Light Estimation

Gray Scale Image Restoration Using Advanced Atmospheric Ligh...

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International conference on image Information processing

作者： Sasmita Mahakud Pradipta Roy EOTS Integrated Test Range (DRDO) Chandipur Balasore Odisha India

visibility of scene is often degraded by different atmospheric phenomena which results in failure of many computer vision applications like outdoor object recognition systems, barrier detection systems, visual surveillance systems, intelligent transportation systems etc. Light coming out from the source and scattered by atmospheric particles towards the camera is the atmospheric light. In many existing image restoration algorithms the results depend on this light. So this paper introduces a image restoration method applied for fog removal which search atmospheric light in a superior way by dividing an image into blocks. Fog decreases slowly from infinite sky regions to the nearer camera regions horizontally downward direction. Consequently atmospheric light is estimated locally in each blocks from upper to lower. The global atmospheric light is the weighted average of all the local atmospheric light. The weight is calculated from histogram of each block. There are many algorithms which suffer from halo effects and edge hammering at the output. In this paper it is rectified by nonlinear filtering which is a pre-processing step. A new edge preserving transmission is also produced using this nonlinear filtering to reduce halo effects. Experimental results are verified and compared qualitatively and quantitatively with the existing haze removal methods. Comparison results shows a better performance in terms of saturated pixels and visual evaluation of different real time scenes.

关键词： image restoration Cameras Histograms Atmospheric modeling image edge detection Filtering Channel estimation

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An Elephant Detection System to Prevent Human-Elephant Conflict and Tracking of Elephant Using Deep Learning

An Elephant Detection System to Prevent Human-Elephant Confl...

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International conference on Information Technology Research (ICITR)

作者： K. S. P. Premarathna R. M. K. T. Rathnayaka J. Charles Sabaragamuwa University of Sri Lanka Belihuloya Sri Lanka

ISBN: (数字)9781665414753

ISBN: (纸本)9781665414760

Human settlement is spreading to forest boundary areas because of the population growth, it triggers disputes between elephants and humans, leading to the loss of property and life. Continuous monitoring and tracking of elephants are difficult due to their large size and movement. Therefore, large-scale for real-time detection and alert of elephant intrusion into human settlements, monitoring is needed. Many methods had been implemented for the elephant's intrusion detection and warning systems. Wildlife conservation and the management of human-elephant conflict require a cost-effective method of monitoring elephant behavior. In this paper, a method for the identification of the elephant as an object using image processing is proposed. The major aim of the study is to minimize the human-elephant conflict in the forest border areas and the conservation of elephants from human activities as well as protect human lives from elephant attacks. We used a data set containing elephants and we developed an approach to distinguish elephants and other animals. We used the Convolutional Neural Network and achieved a maximum accuracy of 94 percent. The proposed method outperformed existing approaches and robustly and accurately detected elephants. It thus can form the basis for a future automated early warning system for elephants.

关键词： Forestry Training Monitoring Classification algorithms Statistics Sociology Real-time systems

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IDOL: A Framework for IMU-DVS Odometry using Lines

IDOL: A Framework for IMU-DVS Odometry using Lines

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2020 IEEE/RSJ International conference on Intelligent Robots and systems (IROS)

作者： Cedric Le Gentil Florian Tschopp Ignacio Alzugaray Teresa vidal-Calleja Roland Siegwart Juan Nieto Autonomous Systems Lab ETH Zurich Switzerland Centre for Autonomous Systems School of Mechanical and Mechatronic Engineering University of Technology Sydney Sydney New South Wales Australia Vision for Robotics Lab ETH Zurich Switzerland

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

In this paper, we introduce IDOL, an optimization-based framework for IMU-DVS Odometry using Lines. Event cameras, also called Dynamic vision Sensors (DVSs), generate highly asynchronous streams of events triggered upon illumination changes for each individual pixel. This novel paradigm presents advantages in low illumination conditions and high-speed motions. Nonetheless, this unconventional sensing modality brings new challenges to perform scene reconstruction or motion estimation. The proposed method offers to leverage a continuous-time representation of the inertial readings to associate each event with timely accurate inertial data. The method's front-end extracts event clusters that belong to line segments in the environment whereas the back-end estimates the system's trajectory alongside the lines' 3D position by minimizing point-to-line distances between individual events and the lines' projection in the image space. A novel attraction/repulsion mechanism is presented to accurately estimate the lines' extremities, avoiding their explicit detection in the event data. The proposed method is benchmarked against a state-of-the-art frame-based visual-inertial odometry framework using public datasets. The results show that IDOL performs at the same order of magnitude on most datasets and even shows better orientation estimates. These findings can have a great impact on new algorithms for DVS.

关键词： Three-dimensional displays Pipelines Lighting Graphics processing units Benchmark testing Trajectory Optimization

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