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Multimedia Systems Studies
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Multimedia Systems Studies

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 April 2025 | Viewed by 3834

Special Issue Editor

Prof. Dr. CheonShik Kim

E-Mail Website
Guest Editor
Department of Computer Engineering, Sejong University, Seoul 05006, Republic of Korea
Interests: multimedia security; multimedia signal processing; image compression; watermark technology; steganography; multimedia database
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Today, general users can enjoy a variety of multimedia content for free as well as for a fee, due to the development of the Internet, personal computers, smart devices, and small IoT devices, and the growth of social media platforms. Most people subscribe to social media platforms and share their content every day, and, accordingly, the amount of multimedia content has grown exponentially. For the growth of multimedia in the future, advances in hardware and software technologies, including the fields mentioned above, and database and multimedia security technologies must be identified. In addition, there may be various issues related to multimedia, such as a problem of appropriately recommending content for personalization services according to personal interests. Another example of technical issues is how to bring the power of well-developed IoT networks to home networks to support multimedia applications. In this Special Issue, researchers and practitioners aim to share various developed ideas related to these issues. We request creative contributions related to multimedia, including, but not limited to, the following topics:

  • Data systems management;
  • Multimedia streaming, interchange, and transmission;
  • Multimedia security, privacy, and right management;
  • Multimedia search and recommendations;
  • Multimedia retrieval and classification;
  • Multimedia home entertainment;
  • Social media computing;
  • Multimedia application;
  • Multimedia communications networks;
  • Network design and configuration for multimedia applications.

Prof. Dr. CheonShik Kim
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • data systems management
  • multimedia streaming, interchange, and transmission
  • multimedia security, privacy, and right management
  • multimedia search and recommendations
  • multimedia retrieval and classification
  • multimedia home entertainment
  • social media computing
  • multimedia application
  • multimedia communications networks
  • network design and configuration for multimedia applications

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Published Papers (3 papers)

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Research

17 pages, 8039 KiB  
Article
A Realistic Hand Image Composition Method for Palmprint ROI Embedding Attack
by Licheng Yan, Lu Leng, Andrew Beng Jin Teoh and Cheonshik Kim
Appl. Sci. 2024, 14(4), 1369; https://doi.org/10.3390/app14041369 - 7 Feb 2024
Cited by 1 | Viewed by 1127
Abstract
Palmprint recognition (PPR) has recently garnered attention due to its robustness and accuracy. Many PPR methods rely on preprocessing the region of interest (ROI). However, the emergence of ROI attacks capable of generating synthetic ROI images poses a significant threat to PPR systems. [...] Read more.
Palmprint recognition (PPR) has recently garnered attention due to its robustness and accuracy. Many PPR methods rely on preprocessing the region of interest (ROI). However, the emergence of ROI attacks capable of generating synthetic ROI images poses a significant threat to PPR systems. Despite this, ROI attacks are less practical since PPR systems typically take hand images as input rather than just the ROI. Therefore, there is a pressing need for a method that specifically targets the system by composing hand images. The intuitive approach involves embedding an ROI into a hand image, a comparatively simpler process requiring less data than generating entirely synthetic images. However, embedding faces challenges, as the composited hand image must maintain a consistent color and texture. To overcome these challenges, we propose a training-free, end-to-end hand image composition method incorporating ROI harmonization and palm blending. The ROI harmonization process iteratively adjusts the ROI to seamlessly integrate with the hand using a modified style transfer method. Simultaneously, palm blending employs a pretrained inpainting model to composite a hand image with a continuous transition. Our results demonstrate that the proposed method achieves a high attack performance on the IITD and Tongji datasets, with the composited hand images exhibiting realistic visual quality. Full article
(This article belongs to the Special Issue Multimedia Systems Studies)
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17 pages, 6833 KiB  
Article
A Regional Brightness Control Method for a Beam Projector to Avoid Human Glare
by Hyeong-Gi Jeon and Kyoung-Hee Lee
Appl. Sci. 2024, 14(4), 1335; https://doi.org/10.3390/app14041335 - 6 Feb 2024
Viewed by 817
Abstract
In this study, we proposed a system to reduce the speaker’s suffering from the strong light of a beam projector by applying regional brightness control over the screen. Since the original image and the projected one on the screen are quite different in [...] Read more.
In this study, we proposed a system to reduce the speaker’s suffering from the strong light of a beam projector by applying regional brightness control over the screen. Since the original image and the projected one on the screen are quite different in area, brightness, and color, the proposed system first transforms them so that they have the same area and similar color tone. Then, to accurately determine the difference between those images, we have introduced a SSIM map, which is a perception-based method of measuring image similarity. Accordingly, an image segmentation model is used to determine the speaker’s silhouette from the SSIM map. We applied a couple of well-trained segmentation models, such as Selfie and DeepLab-v3, provided with MediaPipe. The experimental results showed the operability of the proposed system and that it determines most of a lecturer’s body area on the screen. To closely evaluate the system’s effectiveness, we have measured error rates consisting of false-positive and false-negative errors in the confusion matrix. With the measured results, the error rates appeared so insignificant and stable that the proposed system provides a practical effect for the speakers, especially in the case of applying DeepLab-v3. With the results, it is implied that an accurate segmentation model can considerably elevate the effectiveness of the system. Full article
(This article belongs to the Special Issue Multimedia Systems Studies)
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11 pages, 1421 KiB  
Article
Hourglass 3D CNN for Stereo Disparity Estimation for Mobile Robots
by Thai La, Linh Tao, Chanh Minh Tran, Tho Nguyen Duc, Eiji Kamioka and Phan Xuan Tan
Appl. Sci. 2023, 13(19), 10677; https://doi.org/10.3390/app131910677 - 26 Sep 2023
Viewed by 1276
Abstract
Stereo cameras allow mobile robots to perceive depth in their surroundings by capturing two separate images from slightly different perspectives. This is necessary for tasks such as obstacle avoidance, navigation, and spatial mapping. By utilizing a convolutional neural network (CNN), existing works in [...] Read more.
Stereo cameras allow mobile robots to perceive depth in their surroundings by capturing two separate images from slightly different perspectives. This is necessary for tasks such as obstacle avoidance, navigation, and spatial mapping. By utilizing a convolutional neural network (CNN), existing works in stereo cameras based on depth estimation have achieved superior results. However, the critical requirement for depth estimation for mobile robots is to have an optimal tradeoff between computational cost and accuracy. To achieve such a tradeoff, attention-aware feature aggregation (AAFS) has been proposed for real-time stereo matching on edge devices. AAFS includes multistage feature extraction, an attention module, and a 3D CNN architecture. However, its 3D CNN architecture learns contextual information ineffectively. In this paper, a deep encoder–decoder architecture is applied to an AAFS 3D CNN to improve depth estimation accuracy. Through evaluation, it is proven that the proposed 3D CNN architecture provides significantly better accuracy while keeping the inference time comparable to that of AAFS. Full article
(This article belongs to the Special Issue Multimedia Systems Studies)
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