• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.2 no.1
• /
• pp.3-10
• /
• 1998

In this paper, a new superimposition scheme using a computer vision system was proposed with 7 pairs of skull and ante-mortem photographs, which were already identified through other tests and DNA fingerprints at the Korea National Institute of Scientific Investigation. At this computer vision system, an unidentified skull was caught by video-camcoder with the MPEG and a ante-mortem photograph was scanned by scanner. These two images were processed and superimposed using pixel processing. Recognition of the individual identification by anatomical references was performed on the two superimposed images. This image processing techniques for the superimposition of skull and ante-morterm photographs simplify used the previous approach taking skull photographs and developing it to the same size as the ante-mortem Photographs. This system using various image Processing techniques on computer screen, a more precise and time-saving superimposition technique could be able to be applied in the area of computer individual identification.

• Journal of Broadcast Engineering
• /
• v.24 no.6
• /
• pp.1053-1063
• /
• 2019

Recently, tile-based streaming that transmits one 360 video in several tiles, is actively being studied in order to transmit these 360 video more efficiently. In this paper, for the transmission of high-definition 360 video corresponding to user's viewport in tile-based streaming scenarios, a system of assigning the quality of tiles at each tile by applying the saliency map generated by existing network models is proposed. As a result of usage of Motion-Constrained Tile Set (MCTS) technique to encode each tile independently, the user's viewport was rendered and tested based on Salient360! dataset, streaming 360 video based on the proposed system results in gain to 23% of the user's viewport compared to using the existing high-efficiency video coding (HEVC).

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.5
• /
• pp.339-345
• /
• 2016

In general, mosaic blocks are used to hide some specified areas, such as human faces and disgusting objects, in an input image when images are uploaded on a web-site or blog. This paper proposes a new algorithm for robustly detecting grid mosaic areas in an image based on the edge projection. The proposed algorithm first extracts the Canny edges from an input image. The algorithm then detects the candidate mosaic blocks based on horizontal and vertical edge projection. Subsequently, the algorithm obtains real mosaic areas from the candidate areas by eliminating the non-mosaic candidate regions through geometric features, such as size and compactness. The experimental results showed that the suggested algorithm detects mosaic areas in images more accurately than other existing methods. The suggested mosaic detection approach is expected to be utilized usefully in a variety of multimedia-related real application areas.

• Journal of Broadcast Engineering
• /
• v.27 no.2
• /
• pp.207-215
• /
• 2022

The latest volumetric technology's high geometrical accuracy and realism ensure a high degree of correspondence between the real object and the captured 3D model. Nevertheless, since the 3D model obtained in this way constitutes a sequence as a completely independent 3D model between frames, the consistency of the model surface structure (geometry) is not guaranteed for every frame, and the density of vertices is very high. It can be seen that the interconnection node (Edge) becomes very complicated. 3D models created using this technology are inherently different from models created in movie or video game production pipelines and are not suitable for direct use in applications such as real-time rendering, animation and simulation, and compression. In contrast, our method achieves consistency in the quality of the volumetric 3D model sequence by linking re-meshing, which ensures high consistency of the 3D model surface structure between frames and the gradual deformation and texture transfer through correspondence and matching of non-rigid surfaces. And It maintains the consistency of volumetric 3D model sequence quality and provides post-processing automation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2020.11a
• /
• pp.145-147
• /
• 2020

As deep learning technology advances, there have been many attempts to improve video codecs such as High-Efficiency-Video-Coding (HEVC) using deep learning technology. One of the most researched approaches is improving filters inside codecs through image restoration researches. In this paper, we propose a method 01 replacing the sample adaptive offset (SAO) filtering with a deep neural network. The proposed method uses the deep neural network to find the optimal offset value. The proposed network consists of two subnetworks to find the offset value and its type of the signal, which can restore nonlinear and complex type of error. Experimental results show that the performance is better than the conventional HEVC in low delay P and random access mode.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.39 no.6
• /
• pp.623-629
• /
• 2002

In transmitting compressed video bit-stream over Internet, packet losses cause error propagations in both spatial and temporal domains, which in turn leads to severe degradation I image quality. In this paper, a new error concealment algorithm, called EBMA(Edge Detection based Boundary Matching Algorithm), is proposed to repair damaged portions of the video frames in the receiver. Conventional BMA(Boundary Matching Algorithm) assumes that the pixels on the boundary of the missing block and its neighboring blocks are very similar, but has no consideration of edges across the boundary. In our approach, the edges are detected across the boundary of the lost or erroneous block. Once the orientation of each edge is found, only the pixel difference along the expected edges across the boundary is measured instead of the calculation of difference along the expected edges across the boundary is measured instead of the calculation of differences between all adjacent pixels on the boundary Therefore, the proposed approach needs very few computations and the experiment shows and improvement of the performance over the conventional BMA in terms of both subjective and objective quality of video sequences.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.5
• /
• pp.46-54
• /
• 2011

In this paper, we propose a low-complexity loop filtering method depending on transform-block regions. Block adaptive loop filter (BALF) was developed to improve about 10% in compression performance for the next generation video coding. The BALF employs the Wiener filter that makes reconstructed frames close to the original ones and transmits filter-related information. However, the BALF requires high computational complexity, while it can achieve high compression performance because the block adaptive loop filter is applied to all the pixels in blocks. The proposed method is a new loop filter that classifies pixels in a block into inner and boundary regions based on the characteristics of the integer transform and derives optimum filters for each region. Then, it applies the selected filters for the inner and/or boundary regions. The decoder complexity can be adjusted by selecting region-dependent filter to be used in the decoder side. We found that the proposed algorithm can reduce 35.5% of computational complexity with 2.56% of compression loss, in case that only boundary filter is used.

• Journal of Broadcast Engineering
• /
• v.25 no.3
• /
• pp.325-337
• /
• 2020

Versatile Video Coding (VVC) is a new video coding standard that is being developed by the Joint Video Experts Team of ISO/IEC/ITU-T and it has adopted various technologies including screen content coding tools. Screen contents have a feature that blocks are likely to have diagonal edges like character regions. If triangular partitioning coding is allowed for screen contents having such the feature, coding efficiency would increase. This paper proposes a intra prediction method using triangular partitioning prediction for screen content coding. Similar to the Triangular Prediction Mode of VVC that supports the triangular partitioning prediction, the proposed method derives two prediction blocks using Horizontal and Vertical modes and then it blends the predicted blocks applying masks with triangle shape to generate a final prediction block. The experimental results of the proposed method showed an average of 1.86%, 1.49%, and 1.55% coding efficiency in YUV, respectively, for VVC screen content test sequences.