• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.43-49
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• 2020

This paper proposes a lossless image compression method based on arithmetic coding using block-adaptive Context Tree Weighting. The CTW method predicts and compresses the input data bit by bit. Also, it can achieve a desirable coding distribution for tree sources with an unknown model and unknown parameters. This paper suggests the method to enhance the compression rate about image data, especially aerial and satellite images that require lossless compression. The value of aerial and satellite images is significant. Also, the size of their images is huger than common images. But, existed methods have difficulties to compress these data. For these reasons, this paper shows the experiment to prove a higher compression rate when using the CTW method with divided images than when using the same method with non-divided images. The experimental results indicate that the proposed method is more effective when compressing the divided images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2349-2358
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• 1999

Object-based stereoscopic video coding scheme is presented in this paper. In conventional BMA based stereoscopic video coding for low bit rate transmission, image prediction errors such as block artifacts and mosquito phenomena are occurred. In order to reduce these errors, object based coding scheme is adopted. The proposed scheme consists of preprocessing, object extraction, and object update procedures. The preprocessing procedure extracts non-object regions having low reliability for motion and disparity estimation. This procedure prohibits extracting inaccurate objects. For the better prediction of left channel image, the disparity information is added to the object extraction. And the proposed algorithm can reduce the accumulated error through the object update procedure that detects newly emerging objects, merges objects that have the same object-disparity and object motion, and splits object which has large image prediction error. The experimental results show that the proposed algorithms improve the quality of the prediction without block artifacts and mosquito phenomena.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.1
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• pp.11-18
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• 2001

In this paper, we proposed the image compression algorithm using triangular feature based GHA. In feature extraction, the input images are divided into eight areas of triangular shape, that has positional information for face image compression. The proposed algorithm reduces blocking effects in image reconstruction and contains informations of face feature and shapes of face as input images are divided into eight. We used triangular feature extraction for positional information and GHA for shape information of face images. Simulation results show that the proposed algorithm has a better performance than the block based K-means and non-parsed image based GHA in PSNR at the same bpp.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1996.10a
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• pp.633-636
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• 1996

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.126-133
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• 2003

This paper is related to a morphological segmentation method for extracting the moving object in video sequence using global motion compensation and two-dimensional spatio-temporal entropic thresholding. First, global motion compensation is performed with camera panning vector estimated in the hierarchical pyramid structure constructed by wavelet transform. Secondly, the regions with high possibility to include the moving object between two consecutive frames are extracted block by block from the global motion compensated image using two-dimensional spatio-temporal entropic thresholding. Afterwards, the LUT classifying each block into one among changed block, uncertain block, stationary block according to the results classified by two-dimensional spatio-temporal entropic thresholding is made out. Next, by adaptively selecting the initial search layer and the search range referring to the LUT, the proposed HBMA can effectively carry out fast motion estimation and extract object-included region in the hierarchical pyramid structure. Finally, after we define the thresholded gradient image in the object-included region, and apply the morphological segmentation method to the object-included region pixel by pixel and extract the moving object included in video sequence. As shown in the results of computer simulation, the proposed method provides relatively good segmentation results for moving object and specially comes up with reasonable segmentation results in the edge areas with lower contrast.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1297-1300
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• 2022

Document layout analysis는 문서 이미지의 구조와 구성요소를 파악하는 기술이다. 기존 딥러닝을 사용한 학습 기반 방법에는 각 구성 요소를 검출하는 detection 기반 방식이 많으나 이는 다양한 형식의 문서 이미지에 확장될 수 있는 가능성이 낮다는 한계가 존재한다. 특히, 다양한 모양과 크기의 화학 구조를 포함하는 화학 문서 이미지에 적용하기 어렵다. 본 논문에서는 영상분할을 활용하여 화학 구조 문서를 이해하는 연구를 진행하였다. 기존의 블록 단위로 레이블링된 벤치마크와 다르게 객체 단위로 레이블링한 학습 데이터를 가지고 DeepLabv3 구조의 네트워크를 학습하여 화학 문서 이미지를 효과적으로 분할하였다. 객체 단위 레이블링과 영상 분할을 사용한 방식이 문서 이해 및 화학 구조 검출에 준수한 성능을 보이는 것을 확인하였고 이 방식이 다양한 형식의 문서 이미지에 확장될 수 있음을 보였다.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.11-19
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• 2014

In this paper, we propose a real-time video transcoding scheme for N-Screen service based on cloud computing. This scheme creates an intro-block and several playback blocks by splitting the original video. And there is the first service request, after transmitting the intro-block, transmits the playback blocks that converting the blocks on real-time. In order to completing trans-coding within playback time of each block, we split and allocate the block to node according to performance of each node. Also, in order to provide real-time video playback service, the previous scheme convert original video into all format and resolution. However we show that the proposed scheme can reduce storage usage by converting original video into format with proper resolution suitable to device and platform of client. Through simulation, we show that it is more effective to real-time video playback for N-screen service than the previous method. We also show that the proposed scheme uses less storage usage than previous method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.260-261
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• 2018

MPEG과 VCEG은 차세대 비디오 부호화 표준 기술 개발를 위한 JVET(Joint Video Exploration Team)을 구성하여 현재 비디오 표준화인 HEVC 대비 높은 부호화 효율을 목표로 연구를 진행하며 CfP(Call for Proposal) 단계를 진행 중이다. JVET의 공통 플랫폼인 JEM(Joint Exploration Test Model)은 HEVC의 quad-tree 기반 블록 분할 구조를 대신하여 더 많은 유연성을 제공하는 QTBT(Quad-tree plus binary-tree)가 적용되었다. QTBT는 화면 내 부호화 효율을 높이기 위한 하나의 방법으로 휘도와 색차 신호에 대해 분할된 블록 구조를 지원한다. 이러한 방법은 채널 간 블록 분할 모양이 동일하거나 비슷한 경우에 중복되는 블록 분할 신호가 발생할 수 있는 단점이 있다. 따라서 본 논문에서는 화면 내 부호화에서 채널 간 유사도 비교를 이용하여 적응형 색차 블록 방법을 제안한다. 제안한 방법의 실험 결과로 JEM 6.0과 비교하여 CfE(Call for Evidence) 영상에서 평균 0.28%의 Y BD-rate 감소와 함께 평균 124.5%의 부호화 복잡도 증가를 확인하였다.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.265-270
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• 2011

In this paper, we propose a method for intensity correction using binarization-based region segmentation in 3D stereoscopic images. In the proposed method, 3D stereoscopic right image is segmented using binarizarion. Small regions in the segmented image are eliminated. For each region in right image, a corresponding region in left image is decided through region matching using correlation coefficient. When region-based matching, in order to prevent overlap between regions, we remove a portion of the area closed to the region boundary using morphological filter. The intensity correction in left and right image can be performed through histogram specification between the corresponding regions. Simulation results show the proposed method has the smallest matching error than the conventional method when we generate the right image from the left image using block based motion compensation.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.778-781
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• 2015

The paper presents a new way of visual descriptor for deformable object retrieval on the basis of partition based description. The proposed descriptor technology partitions a given object into boundary area and interior area and extracts a descriptor from each area. The final descriptor combines these descriptors. From a given image, deformable object is segmented. The center position of the deformable object is calculated. The object is partitioned into N × N blocks on the basis of the given center position. Blocks are classified as boundary area and interior area depending on the pixels in the block. The proposed descriptor consists of extracted MPEG-7 dominant descriptors from both the boundary and interior area. The performance of proposed method is tested on a database of 1,973 handbag images constructed with view point changes. ARR (Average Retrieval Rate) is used for the retrieval accuracy of the proposed algorithm, compared with MPEG-7 dominant color descriptor.