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QMCS-IAS: Quantum mechanism and compression sensing-based image authentication and security technique

Multimedia Tools and Applications 2024年 1-27页

作者： Singh, Ranjeet Kumar Tripathi, Kuldeep Narayan Kaur, Gagandeep Agrawal, Rohit Department of Computer Science and Engineering Madhav Institute of Technology & ampScience Race Course Road MP Gwalior474005 India

Ensuring the security and protection of digital content transmitted over a network is a critical challenge, as data can take various forms, such as text, images, audio, and videos, all of which can be easily manipulated by hackers. Watermarking is one of the practical approaches to address data authentication, copyright protection, and document ownership issues. The primary objective of this research is to develop hybrid watermark encryption and as well as compression of watermark embedding mechanism that ensures secure and efficient watermarking of images using quantum chaos maps and discrete wavelet transformation. This study also introduces a novel dual watermarking approach combining quantum chaos-based encryption and discrete wavelet transformation to achieve robust watermark embedding, also its maintain the capacity of watermarked images. The method involves encrypting watermark components using measurement matrices derived from quantum chaos maps, followed by pixel exchange procedures and embedding into specific frequency sub-bands of the host image, thereby enhancing both the security and quality of watermarking. The objective of this work is to maintain the capacity of watermarked images during the dual embedding process using a compression mechanism. Experimental results show the proposed approach consistently outperforms the existing approach in terms of watermark image quality and robustness. The correlation coefficient (CC) coefficients for the proposed algorithm generally range between 0.95 and 0.99, indicating superior watermark preservation and retrieval capabilities. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Pixels

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Investigation of system-driven talking approaches using depth and color image information for digital signage with speech user interface 13

Investigation of system-driven talking approaches using dept...

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Takahashi, Kuuta Kawamoto, Shinichi Gunma College Advanced Production Systems Engineering Course Maebashi Japan Gunma College Department of Information and Computer Engineering Maebashi Japan

ISBN: (纸本)9798350355079

In recent decades, digital signages have been widely used. Specifically, digital signages that have a purpose of either providing information or advertising, it is important to direct people's attention toward that information. Conventionally, some approaches to attract viewer's attention include using animation and audible information such as playing background music or a flashing a catchphrase. However, language information has not been implemented in these approaches. In this study, we propose a method to call out a specific person to the front of a digital signage by using color images and depth information. By calling out a specific person by using this method, it is expected for this person to have an awareness that they are a target intended by a digital signage. In this study, we conducted experiments that use utterances based on a person's position, distance from a digital signage, clothing colors, or a pair of two features. Based on the study results, we confirm that a pair of features, that is, clothing color and depth, is the most effective to call out a specific person to the front of a digital signage © 2024 IEEE.

关键词： User interfaces

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Wheel Arrangement of a Rocker-bogie Mechanism with Omni-directional Wheels for Reduced DOF Design

Wheel Arrangement of a Rocker-bogie Mechanism with Omni-dire...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Tokudome, Yusuke Yamamoto, Yuya Watanabe, Yuta Uahchinkul, Chinvudh Muramatsu, Satoshi Inagaki, Katsuhiko Tokai University Course of Electrical and Electronic Engineering Kanagawa259-1292 Japan Tokai University Course of Science and Technology Kanagawa259-1292 Japan Tokai University Department of Applied Computer Engineering Kanagawa259-1292 Japan

ISBN: (纸本)9798331531614

Wheeled mobile mechanisms are essentially unsuitable for moving over rough terrain, but the rocker bogie mechanism is known as a six-wheeled mobile mechanism with high ground adaptability that solves this problem. However, this mechanism requires a large number of degrees of freedom (DOF), at least 10 DOF, or 12 DOF in the case of an omni-directional moving function. This contains problems in terms of control system configuration, mechanism development, and energy efficiency. In this study, the number of DOFs is reduced to a maximum of 6 DOFs and a minimum of 4 DOFs by applying omni-directional wheels to the rocker bogie mechanism. First, we examined how the two main types of omni-directional wheels should be arranged in relation to the six wheels. Based on the results, an actual machine was developed for evaluation, and its effectiveness was confirmed through step over experiment on several types of stairs. © 2025 IEEE.

关键词： Bogies (railroad rolling stock)

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CbcErDL: Classification of breast cancer from mammograms using enhance image reduction and deep learning framework

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Multimedia Tools and Applications 2025年第15期84卷 15501-15526页

作者： Agrawal, Rohit Singh, Navneet Pratap Shelke, Nitin Arvind Tripathi, Kuldeep Narayan Singh, Ranjeet Kumar Department of Computer Science and Engineering Madhav Institute of Technology & Science Race Course Road MP Gwalior474005 India School of AI Bennett University Uttar Pradesh Greater Noida201310 India School of Computer Science and Engineering Bennett University TechZone 2 UP Greater Noida201310 India

Breast cancer is a major health concern for women worldwide, and early detection is vital to improve treatment outcomes. While existing techniques in mammogram classification have demonstrated promising results, their limitations become apparent when applied to larger datasets. The decline in performance with increased dataset size highlights the need for further research and advancements in the field to enhance the scalability and generalizability of these techniques. In this study, we propose a framework to classify breast cancer from mammograms using techniques such as mammogram enhancement, discrete cosine transform (DCT) dimensionality reduction, and deep convolutional neural network (DCNN). The first step is to improve the mammogram display to improve the visibility of key features and reduce noise. For this, we use 2-stage Contrast Limited Adaptive Histogram Equalization (CLAHE). DCT is then used to enhance mammograms to reduce residual data. It can provide effective reduction while preserving important diagnostic information. In this way, we reduce the computational complexity and increase the results of subsequent classification algorithms. Finally, DCNN is used on size-reduced DCT coefficients to learn feature discrimination and classification of mammograms. DCNN architectures have been optimized with various techniques to improve their performance, including regularization and hyperparameter tuning. We perform experiments on the DDSM dataset, a large dataset containing approximately 55,000 mammogram images, and demonstrate the effectiveness of the proposed method. We assess the proposed model’s performance by computing the precision, recall, accuracy, F1-Score, and area under the receiver operating characteristic curve (AUC). We achieve Precision and Recall values of 0.929 and 0.963, respectively. The classification accuracy of the proposed models is 0.963. Moreover, the F1-Score and AUC values are 0.962 and 0.987, respectively. These results are better a

关键词： Discrete cosine transforms

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Depth Estimation with Tilted Optics Using Split Color Filter Aperture 4

Depth Estimation with Tilted Optics Using Split Color Filter...

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4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Fukino, Aoi Ikeoka, Hiroshi Hamamoto, Takavuki Graduate School of Engineering Fukuyama University Information Processing Engineering Course Hiroshima Japan Fukuyama University Faculty of Engineering Department of Computer Science Hiroshima Japan

ISBN: (纸本)9798350395914

Camera-based depth estimation methods are useful for various automobile applications. For example, depth estimation methods based on stereo cameras triangulate the depth between objects and cameras. However, they are susceptible to baseline distortion owing to vibrations, aging, and thermal expansion. On the contrary, depth estimation methods based on a monocular camera, such as depth-from-defocus, use a focusing mechanism or spectroscopic optics to calculate the depth from the difference of defocus images. However, because the change in sharpness, which is the inverse of defocus, is slightly in the depth direction, it is unsuitable for deep-range estimation. Therefore, we are developing depth-estimation methods that use a monocular camera with special focus images obtained through tilted optics, which have no baseline distortion problem and have a deep estimation range. When tilted optics are used, the plane of sharp focus (POF) appears tilted, while the depth of field (DOF) lies and increases toward the depth direction. Moreover, to allow for the use of only one image-sensor, a one-shot, we studied a depth estimation method using tilted optics with two different aperture sizes for each color wavelength by introducing concentric color filter apertures. However, as with conventional methods, the Gaussian sharpness model does not strictly fit to the actual sharpness, resulting in reduced estimation accuracy. In this study, we propose a method for high-speed and high-accuracy depth estimation that involves adding a split color filter aperture to a tilted optic and using a different sharpness model for each DOF side. © 2024 IEEE.

关键词： Stereo image processing

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Development of a Novel Mechanical Layer Jamming Cable-driven Soft Actuator for Soft Gripper System

Development of a Novel Mechanical Layer Jamming Cable-driven...

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2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Uahchinkul, Chinvudh Muramatsu, Satoshi Inagaki, Katsuhiko Tokai University Course of Science and Technology Kanagawa259-1292 Japan Tokai University Department of Applied Computer Engineering Kanagawa259-1292 Japan

ISBN: (纸本)9798331531614

Soft actuators have many advantages, such as flexibility and safe interaction with the environment. Despite these advantages, they still lack the stiffness to carry the high load. The layer jamming mechanism can be applied to the actuator to increase stiffness, and a vacuum can control the stiffness of the mechanism. However, the typical jamming mechanism has a risk of air leakage, and vacuums are bulky to some systems. In order to solve this problem, we have developed a novel mechanical layer jamming for the cable-driven soft actuator in this paper. Our design uses the actuator body to generate the compression force to the layer at the middle of the actuator's body to increase the actuator's stiffness. The result shows the effectiveness of our mechanical layer jamming in increasing the stiffness of the actuator when adding the load to the tip of the actuator. In addition, we have applied our actuator to the soft gripper system, which successfully grasped various objects and changed the stiffness of the actuator. © 2025 IEEE.

关键词： Grippers

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Maneuverability Improvement by Feedback Compensation of a Physically Human-Interacting Robot with Variable Damping Control

Maneuverability Improvement by Feedback Compensation of a Ph...

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18th IEEE International Conference on Advanced Motion Control, AMC 2024

作者： Songthumjitti, Narawich Inara, Takpeshi Graduate School of Tokai University Course of Electrical and Electronic Engineering Kanagawa Japan Tokai University Department of Applied Computer Engineering Kanagawa Japan

ISBN: (纸本)9798350342819

Manufacturing workflows can be enhanced using the implementation of robots;however, it is limited to repetitive tasks, and a human operator is still needed to gain flexibility in the robot's movement. However, human-robot interaction can cause instability due to the robot's characteristics. The typical solution is to decrease the admittance parameter, but it also reduces the assisting effectiveness. Variable damping is another way to counter this problem, but if the instability problem isn't solved yet, the effect can be difficult to perceive. Our study aims to implement feedback compensation in the robot system to reduce the effect of actuator dead time and insufficient structural stiffness. The results prove that the implementation of feedback compensation can greatly improve the maneuverability of the robot by decreasing the force required during the traveling phase and increasing accuracy in the positioning phase, resulting in a task that can be completed with less effort and a shorter operation time. © 2024 IEEE.

关键词： Human robot interaction

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Distance Characteristics of Power Absorption Ratio of the Skin Based on Sommerfeld's Theory 7

Distance Characteristics of Power Absorption Ratio of the Sk...

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7th IEEE Global Electromagnetic Compatibility Conference, GEMCCON 2023

作者： Sato, Ken Kamimura, Yoshitsugu National Institute of Technology Hachinohe College Electrical and Computer Engineering Course Hachinohe Japan Graduate School of Engineering Utsunomiya University Division of Engineering and Agriculture Utsunomiya Japan

ISBN: (纸本)9798350396935

The dependence of the amount of power absorbed by the skin on the distance from the small antenna was analyzed based on the theory of Sommerfeld and Renner. The results showed good agreement between the theoretical and numerical values, with all power absorbed at small separation distance and converging to about 20 % at larger distance. © 2023 IEEE.

关键词： Antennas

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Privacy Concerns from Single-Word Search Query Leakage from Web Browsers Through DNS

IEEE Networking Letters

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IEEE Networking Letters 2022年第1期4卷 48-52页

作者： Isobe, Katsuki Kondo, Daishi Tode, Hideki Computer Science Course College of Engineering Osaka Prefecture University Sakai599-8531 Japan Department of Computer Science and Intelligent Systems Graduate School of Engineering Osaka Prefecture University Sakai599-8531 Japan

Some Web browsers working on certain operating systems (OSs) specify that a single-word search query entered into the search bar be sent to the recursive resolver of the domain name system (DNS) as a DNS request that includes the word. Such behavior is unexpected for users and induces privacy concerns through single-word search query leakage. We present our survey on the conditions during which this behavior occurs. By analyzing the DNS traffic captured at the recursive resolvers, we demonstrate that a considerable number of queries are leaked and the interests of individuals or organizations can be inferred through passive eavesdroppers. © 2019 IEEE.

关键词： Search engines

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Automatic Identification of Daily Life Activities and Prediction of Falling Accidents Caused by Behavior 25th

Automatic Identification of Daily Life Activities and Pred...

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25th International Conference on Human-computer Interaction, HCII 2023

作者： Hayashi, Seiji Nakajima, Akira Department of Electronics and Computer Systems Faculty of Engineering Takushoku University Tokyo Japan Mechanical and Electronic Systems Course Graduate School of Engineering Takushoku University Tokyo Japan

ISBN: (纸本)9783031359910

In the present research, we developed an application that measures acceleration by a smartphone located at the waist, along with a deep learning system that automatically detects six behavioral activities (walking, running, standing, walking downstairs, walking upstairs, and falling). Specifically, we use a human activity database provided by the University of California–Irvine (UCI) to create a deep learning model with the UCI data. Next, transfer learning was applied to the learning model for the measurement data obtained by the acceleration acquisition application developed in this research. Using Sony’s Neural Network Console development environment as a deep learning tool, in recognition experiments, our proposed method for automatic identification of activities and prediction of falling accidents caused by behavior achieved a high accuracy rate of almost 95%. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Deep learning

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