• The Journal of Korean Institute of Information Technology
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• v.17 no.10
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• pp.101-113
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• 2019

Recently, the intelligent video surveillance technology has become able to provide various services such as predictive surveillance that have not been provided previously. Securing the security of the intelligent video surveillance is essential, and malicious manipulation of the original CCTV video data can lead to serious social problems. Therefore, in this paper, we proposed an intelligent video surveillance environment based on blockchain. The proposed scheme guarantees the integrity of the CCTV image data and protects the ROI privacy through the edge blockchain, so there is no privacy exposure of the object. In addition, it is effective because it is possible to increase the transmission efficiency and reduce storage by enabling video deduplication.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1976-1985
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• 2015

The amount of packets in palyout buffer of video streaming receiver can be changed by network condition, and saturated and exhausted by the delay and jitter. Especially, if the amount of incoming video traffic exceeds the maximum allowed playout buffer, buffer overflow problem can be generated. It makes the deterioration of video image and the discontinuity of playout by skip phenomenon. Also, if the incoming packets are delayed by network confusion, the stop phenomenon of video image is made by buffering due to buffer underflow problem. To solve these problems, this paper proposes the video streaming receiver with token bucket scheme which automatically establishes the important parameters like token generation rate r and bucket maximum capacity c adapting to the pattern of video packets. The simulation results using network simulator-2 (NS-2) and joint scalable video model (JSVM) show that the proposed token bucket scheme with automatic establishment parameter provides better performance than the existing token bucket scheme with manual establishment parameter in terms of the generation number of overflow and underflow, packer loss rate, and peak signal to noise ratio (PSNR) in three test video sequences.

• Journal of Communications and Networks
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• v.6 no.4
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• pp.387-396
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• 2004

One of the main problems associated with MANETs is that mobility and the associated route discovery and maintenance procedures of reactive routing protocols cause severe interruptions on real-time video streams. Some of these interruptions are too large to be concealed using any sort of video technology, resulting in communications breaks unpleasant for the final end user. We present a solution for enhanced video transmission that increases route stability by using an improved route discovery process based on the DSR routing protocol, along with traffic splitting algorithms and a preventive route discovery mechanism. We also present some video adaptative mechanisms that improve the overall performance of multipath routing in terms of video data replication and video packet splitting strategies. Combining our proposals, we achieve up to 97% less interruptions on communication with high mobility and over 1.2 dB of improvements in terms of video distortion.

• Journal of Korea Multimedia Society
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• v.22 no.7
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• pp.770-779
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• 2019

Video coding technologies are progressively becoming more efficient and complex. The Versatile Video Coding (VVC) is a new state-of-the art video compression standard that is going to be a standard, as the next generation of High Efficiency Video Coding (HEVC) standard. To explore the future video coding technologies beyond the HEVC, numerous efficient methods have been adopted by the Joint Video Exploration Team (JVET). Since then, the next generation video coding standard named as VVC and its software model called VVC Test Model (VTM) have emerged. In this paper, several important coding features for motion estimation and motion compensation in the VVC standard is introduced and analyzed in terms of the performance. Improved coding tools introduced for ME and MC in VVC, can achieve much better and good balance between coding efficiency and coding complexity compared with the HEVC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.382-403
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• 2020

Steganography is the art of concealing the existence of a secret data in a non-secret digital carrier called cover media. While the image of steganography methods is extensively researched, studies on other cover files remain limited. Videos are promising research items for steganography primitives. This study presents an improved approach to video steganography. The improvement is achieved by allowing senders and receivers exchanging secret data without embedding the hidden data in the cover file as in traditional steganography methods. The method is based mainly on searching for exact matches between the secret text and the video frames RGB channel pixel values. Accordingly, a random key-dependent data is generated, and Elliptic Curve Public Key Cryptography is used. The proposed method has an unlimited embedding capacity. The results show that the improved method is secure against traditional steganography attacks since the cover file has no embedded data. Compared to other existing Steganography video systems, the proposed system shows that the method proposed is unlimited in its embedding capacity, system invisibility, and robustness. The system achieves high precision for data recovery in the receiver. The performance of the proposed method is found to be acceptable across different sizes of video files.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3239-3267
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• 2018

Image and video dehazing is a popular topic in the field of computer vision and digital image processing. A fast, optimized dehazing algorithm was recently proposed that enhances contrast and reduces flickering artifacts in a dehazed video sequence by minimizing a cost function that makes transmission values spatially and temporally coherent. However, its fixed-size block partitioning leads to block effects. The temporal cost function also suffers from the temporal non-coherence of newly appearing objects in a scene. Further, the weak edges in a hazy image are not addressed. Hence, a video dehazing algorithm based on well designed spectral clustering is proposed. To avoid block artifacts, the spectral clustering is customized to segment static scenes to ensure the same target has the same transmission value. Assuming that edge images dehazed with optimized transmission values have richer detail than before restoration, an edge intensity function is added to the spatial consistency cost model. Atmospheric light is estimated using a modified quadtree search. Different temporal transmission models are established for newly appearing objects, static backgrounds, and moving objects. The experimental results demonstrate that the new method provides higher dehazing quality and lower time complexity than the previous technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3204-3220
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• 2021

We perform the task of video object segmentation by incorporating a conditional random field (CRF) and convolutional neural networks (CNNs). Most methods employ a CRF to refine a coarse output from fully convolutional networks. Others treat the inference process of the CRF as a recurrent neural network and then combine CNNs and the CRF into an end-to-end model for video object segmentation. In contrast to these methods, we propose a novel higher-order CRF model to solve the problem of video object segmentation. Specifically, we use CNNs to establish a higher-order dependence among pixels, and this dependence can provide critical global information for a segmentation model to enhance the global consistency of segmentation. In general, the optimization of the higher-order energy is extremely difficult. To make the problem tractable, we decompose the higher-order energy into two parts by utilizing auxiliary variables and then solve it by using an iterative process. We conduct quantitative and qualitative analyses on multiple datasets, and the proposed method achieves competitive results.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.182-185
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• 2019

This paper analyzes performances of modules in implementing a programmable multi-format video decoder. The goal of the proposed platform is the high-end Full High Definition (FHD) video decoder. The proposed multi-format video decoder consists of a reconfigurable processor, dedicated bit-stream co-processor, memory controller, cache for motion compensation, and flexible hardware accelerators. The experiments suggest performance baseline of modules for the proposed architecture operating at 300 MHz clock with capability of decoding HEVC bit-streams of FHD 30 frames per second.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.75-81
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• 2023

Video platforms, including YouTube, have a structure in which the number of video views is directly related to the publisher's profits. Therefore, video publishers induce viewers by using provocative titles and thumbnails to garner more views. The conventional technique used to limit such harmful videos has low detection accuracy and relies on follow-up measures based on user reports. To address these problems, this study proposes a technique to improve the accuracy of filtering harmful media using thumbnails, titles, and audio data from videos. This study analyzed these three pieces of multimodal information; if the number of harmful determinations was greater than the set threshold, the video was deemed to be harmful, and its upload was restricted. The experimental results showed that the proposed multimodal information extraction technique used for harmfulvideo filtering achieved a 9% better performance than YouTube's Restricted Mode with regard to detection accuracy and a 41% better performance than the YouTube automation system.

• ETRI Journal
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• v.44 no.1
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• pp.38-50
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• 2022

This paper presents a study on the use of encoder-derived features in decoder-side depth estimation. The scheme of multiview video encoding does not require the transmission of depth maps (which carry the geometry of a three-dimensional scene) as only a set of input views and their parameters are compressed and packed into the bitstream, with a set of features that could make it easier to estimate geometry in the decoder. The paper proposes novel recursive block splitting for the feature extraction process and evaluates different scenarios of feature-driven decoder-side depth estimation, performed by assessing their influence on the bitrate of metadata, quality of the reconstructed video, and time of depth estimation. As efficient encoding of multiview sequences became one of the main scopes of the video encoding community, the experimental results are based on the "geometry absent" profile from the incoming MPEG Immersive video standard. The results show that the quality of synthesized views using the proposed recursive block splitting outperforms that of the state-of-the-art approach.