• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.141-142
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• 2015

본 논문에서는 HEVC(High Efficiency Video Coding)을 위한 고속 부호화 알고리즘을 제안한다. 제안 방법은 HEVC 의 화면내 부호화 과정에서 주변 부호화 모드 정보인 MPM(Most Probable Mode)과 RMD(Rough Mode Decision) 과정의 결과로 얻어지는 후보 모드들의 상관관계를 이용하여 높은 계산 복잡도를 가지는 RDO(Rate-Distortion Optimization) 과정이 고려하는 후보의 개수를 줄여 전체 부호화기의 부호화 복잡도를 낮춘다. 실험 결과에서는 제안 방법이 약 0.29% BD-rate 의 부호화 손실만으로 20.43%의 부호화 복잡도를 감소시켰음을 보인다.

• Journal of the Semiconductor & Display Technology
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• v.12 no.3
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• pp.13-18
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• 2013

Motion estimation is a key technique of modern video processing that significantly improves the coding efficiency significantly by exploiting the temporal redundancy between successive frames. Thread-level parallelism is a promising method to accelerate the motion estimation process for multithreading general-purpose processors. In this paper, we propose a parallel motion estimation algorithm which parallelizes the motion search process of the current H.264/AVC encoder. The proposed algorithm is implemented using the OpenMP application programming interface (API) and can be easily integrated into the current encoder. The experimental results show that the proposed parallel algorithm can reduce the processing time of the motion estimation up to 65.08% without any penalty in the rate-distortion (RD) performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.3B
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• pp.295-301
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• 2001

전송과정에서 발생하는 왜곡량에 따라 전송률의 하한이 결정되는 율-왜곡 이론은 시간적으로 민감한 부분을 왜곡없이 부호화하여 전송하는 영상 시스템에서 기본이 되는 중요한 요소이다. 율-왜곡 이론은 정보량의 개념으로부터 시작되어 원 신호의 확률분포와 왜곡의 측정기준에 의해 결정되는데, 이 논문에서는 가우시안과 라플라시안 분포함수에 절대치 오차기준과 자승 오차기준을 적용하여 율-왜곡 함수를 각각 구하였다. 나아가서 저전송률 부호기로 개발된 H.263 부호기에 이 함수를 적용하여 분석하였다. 비교를 위해 자승 오차기준에 위한 이론치와 실제 측정치를 제시하였다. H.263 부호기는 엔트로피 부호화, 부호화를 블록 패턴 등 다양한 기법을 사용하여 율-왜곡 함수에 의한 이론치보다 주어진 MSE에서 정규화 비트율이 최대 0.55만큼 더 낮은 전송률을 얻을 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.385-405
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• 2019

High Efficiency Video Coding (HEVC) enables significantly improved compression performance relative to existing standards. However, the advance also requires high computational complexity. To accelerate the intra prediction mode decision, a minimum risk Bayesian classification framework is introduced. The classifier selects a small number of candidate modes to be evaluated by a rate-distortion optimization process using the sum of absolute Hadamard transformed difference (SATD). Moreover, the proposed method provides a loss factor that is a good trade-off model between computational complexity and coding efficiency. Experimental results show that the proposed method achieves a 31.54% average reduction in the encoding run time with a negligible coding loss of 0.93% BD-rate relative to HEVC test model 16.6 for the Intra_Main common test condition.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.118-119
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• 2019

본 논문에서는 비디오 제작 및 유통의 활성화에 따라 필요성이 높아지고 있는 장면 전환을 검출하는 방법을 제안한다. 유통 과정에서 해상도 변환, 자막 삽입, 압축, 영상 반전 등의 다양한 변형이 추가되더라도 동일하게 장면 전환을 검출해야 하므로 전처리 과정과 SIFT를 이용한 특징 추출, 변형을 고려한 매칭 방법을 이용하여 프레임 간의 매칭률을 계산한다. 또한 매칭률의 임계값을 기준으로 장면 전환 여부를 판단한다. 원본 비디오에서의 특징을 가지고 다양한 변형이 가해진 비디오에서의 특징과 매칭률을 계산하여 유효성을 판단한다.

• Electronics and Telecommunications Trends
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• v.37 no.5
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• pp.22-32
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• 2022

Optical character recognition is a primary technology required in different fields, including digitizing archival documents, industrial automation, automatic driving, video analytics, medicine, and financial institution, among others. It was created in 1928 using pattern matching, but with the advent of artificial intelligence, it has since evolved into a high-performance character recognition technology. Recently, methods for detecting curved text and characters existing in a complicated background are being studied. Additionally, deep learning models are being developed in a way to recognize texts in various orientations and resolutions, perspective distortion, illumination reflection and partially occluded text, complex font characters, and special characters and artistic text among others. This report reviews the recent deep learning-based text detection and recognition methods and their various applications.

• Annual Conference of KIPS
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• 2011.04a
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• pp.986-989
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• 2011

Reversible data hiding is a technique that can embed information into cover media (image, video, voice signal) and can recover the original cover media after extracting the embedded information. In this papa, we propose a new reversible data hiding methods that based on block median preservation and the image local characteristic. By using the median value of a block, a high payload can be got and by considering the image local characteristic, a lot of distortion can be avoided and a high PSNR can be got. In the experiment, our methods can generate better result than the previous reversible data hiding methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.146-149
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• 2022

기존 RDO(Rate Distortion Optimization) 기반 압축 방식은 압축 성능에 초점을 두기 때문에 영상 내 인지 특성이 무시될 수 있다. 따라서 RoI(Region of Interest)을 기반으로 압축률을 조절하는 연구가 고안[1, 2, 3, 4] 되었으며, HVS(Human Visual System) 관점에서 영상 내 중요한 부분에 대해 더 높은 품질로 영상을 압축하는 연구가 대부분이다. 최근 인공지능 기술이 발전함에 따라 지능형 영상 분석에 대한 수요가 증가하고 있으며, 이에 따라 머신 비전을 위한 영상 부호화 및 효율적인 전송에 대한 필요성이 대두되고 있다. 본 논문에서는 VVC(Versatile Video Coding)의 dQP(delta Quantization Parameter)를 활용하여 RoI(Region of Interest) 기반압축 방법을 제안하고, 두가지의 RoI 추출 방식을 소개한다. Detectron2 Faster R-CNN X101-FPN [5]의 첫번째 탐지기를 통해 후보 영역 기반 RoI 을 추출하고, 두번째 탐지기를 통해 객체 기반 RoI 을 추출하여, 영상 내 객체 부분과 비객체 부분으로 나누어 서로 다른 압축률로 압축을 수행하였으며, 이에 따른 성능을 비교하고자 한다.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.144-153
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• 2009

Recently, as the necessity of a light-weighted video encoding technique has been rising for applications such as UCC(User Created Contents) or Multiview Video, Distributed Video Coding(DVC) where a decoder, not an encoder, performs the motion estimation/compensation taking most of computational complexity has been vigorously investigated. Wyner-Ziv coding reconstructs an image by eliminating the noise on side information which is decoder-side prediction of original image using channel code. Generally the side information of Wyner-Ziv coding is generated by using frame interpolation between key frames. The channel code such as Turbo code or LDPC code which shows a performance close to the Shannon's limit is employed. The noise model of Wyner-Ziv coding for channel decoding is called Virtual Channel Noise and is generally modeled by Laplacian or Gaussian distribution. In this paper, we propose a Wyner-Ziv coding method based on the frequency-adaptive channel noise modeling in transform domain. The experimental results with various sequences prove that the proposed method makes the channel noise model more accurate compared to the conventional scheme, resulting in improvement of the rate-distortion performance by up to 0.52dB.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.510-519
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• 2011

Intra mode decision is a useful coding tool in Distributed Video Coding (DVC) for improving DVC coding efficiency for video sequences having fast motion. A major limitation associated with the existing intra mode decision methods, however, is that its efficiency highly depends on user-specified thresholds or modeling parameters. This paper proposes an entropy-based method to address this problem. The probabilities of intra and Wyner?Ziv (WZ) modes are determined firstly by examining correlation of pixels in spatial and temporal directions. Based on these probabilities, entropy of the intra and the WZ modes are computed. A comparison based on the entropy values decides a coding mode between intra coding and WZ coding without relying on any user-specified thresholds or modeling parameters. Experimental results show its superior rate-distortion performance of improvements of PSNR up to 2 dB against a conventional Wyner?Ziv coding without intra mode decision. Furthermore, since the proposed method does not require any thresholds or modeling parameters from users, it is very attractive for real life applications.