• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.60-65
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• 2010

This paper describes the results of 2D mapping, feature detection and matching to create the surrounding environment in the mounted stereo camera on Mobile robot. Extract method of image's feature in real-time processing for quick operation uses the edge detection and Sum of Absolute Difference(SAD), stereo matching technique can be obtained through the correlation coefficient. To estimate the location of a mobile robot using ZigBee beacon and encoders mounted on the robot is estimated by Kalman filter. In addition, the merged gyro scope to measure compass is possible to generate map during mobile robot is moving. The Simultaneous Localization and Mapping (SLAM) of mobile robot technology with an intelligent robot can be applied efficiently in human life would be based.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.12-14
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• 2014

본 논문에서는 AZB (All-Zero Block) 검출을 이용한 조기 부호화 단위(Coding Unit, CU) 결정 방법을 제안한다. HEVC 영상 코덱의 하드웨어 구현에서 이산여현변환(DCT)는 많은 부호화 자원을 필요로 하는 과정으로 DCT 수행 이전에 블록 내의 모든 양자화 계수가 0 이 되는 영블록(All-zero Block)을 미리 검출하여 DCT 및 양자화 과정을 생략하고 CU 의 부호화 과정을 조기에 종료함으로써 부호화 복잡도를 크게 감소시키는 방법을 제안한다. 기존의 SAD (Sum of Absolute Difference) 또는 SATD (Sum of Absolute Transform Difference)에 기반하는 AZB 검출 방법은 HEVC 에서 새롭게 추가된 큰 크기의 $16{\times}16$와 $32{\times}32$ DCT 에서 AZB 을 효율적으로 검출할 수 없는 한계가 존재한다. 본 논문에서는 DCT 변환 커널이 하다마드 변환 커널과 또 다른 정규 직교 변환 커널로 분할하여 표현할 수 있는 성질을 이용하여, 부화소 움직임벡터 추정 과정을 통해 생성된 하드마드 변환 계수에 DCT 를 생성하는 변환 커널을 곱하여 DCT 변환 커널을 생성한 후 양자화 계수를 이용하여 CU 단위의 AZB 을 검출하는 방법을 제안한다. 또한 AZB 검출과 움직임 벡터의 크기를 이용하여 현재 CU 의 부호화 과정을 조기에 종료하는 방법을 제안한다. 제안하는 AZB 검출과 CU 조기 종료 부호화 방법을 사용하면 평균적으로 34.7%의 부호화 시간을 감소시켜 부호화 복잡도를 크게 줄일 수 있다.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.311-316
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• 2009

This paper presents the motion estimation algorithm on real-time for mobile surveillance robot using particle filter. the particle filter that based on the monte carlo's sampling method, use bayesian conditional probability model which having prior distribution probability and posterior distribution probability. However, the initial probability density was set to define randomly in the most of particle filter. In this paper, we find first the initial probability density using Sum of Absolute Difference(SAD). and we applied it in the partical filter. In result, more robust real-time estimation and tracking system on the randomly moving object was realized in the mobile surveillance robot environments.

• Journal of Broadcast Engineering
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• v.7 no.4
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• pp.317-326
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• 2002

The adaptive coding schemes in H.264 standardization provide a significant ceding efficiency and some additional features like error resilience and network friendliness. The variable block size motion compensation using multiple reference frames is one of the key H.264 coding elements to provide main performance gain, but also the main culprit that increases the overall computational complexity. For this reason, this paper proposes a selective motion estimation algorithm based on variable block size for fast motion estimation in H.264. After we find the SAD(Sum of Absolute Difference) at initial points using diamond search, we decide whether to perform additional motion search in each block. Simulation results show that the proposed method is five times faster than the conventional full search in case of search range $\pm$32.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.107-115
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• 2014

The reduced-bit transform based bit-plane matching algorithm (BPM) can obtain the block matching result through its simple calculation and hardware design compared to the conventional block matching algorithms (BMAs), but the block matching accuracy of BPMs is somewhat low. In this paper, reduced-bit transform based sum of the absolute difference (R-SAD) is proposed to improve the block matching accuracy in comparison with the conventional BPMs and it is shown that the matching process can be obtained using the logical operations. Firstly, this method transforms the current and the reference images into their respective 2-bit images and then a truth table is obtained from the relation between input and output 2-bit images. Next, a truth table is simplified by Karnaugh map and the absolute difference is calculated by using simple logical operations. Finally, the simulation results show that the proposed R-SAD can obtain higher accuracy in block matching results compared to the conventional BPMs through the PSNR analysis in the motion compensation experiments.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.98-113
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• 2002

In this paper, we present advanced algorithms to reduce the computations of block matching algorithms for motion estimation in video coding. Advanced multi-level successive elimination algorithms(AMSEA) are based on the Multi-level successive elimination algorithm(MSEA)[1]. The first algorithm is that when we calculate the sum of absolute difference (SAD) between the sum norms of sub-blocks in MSEA, we use the partial distortion elimination technique. By using the first algorithm, we can reduce the computations of MSEA further. In the second algorithm, we calculate SAD adaptively from large value to small value according to the absolute difference values between pixels of blocks. By using the second algorithm, the partial distortion elimination in SAD calculation can occur early. So, the computations of MSEA can be reduced. In the third algorithm, we can estimate the elimination level of MSEA. Accordingly, the computations of the MSEA related to the level lower than the estimated level can be reduced. The fourth algorithm is a very fast block matching algorithm with nearly 100% motion estimation accuracy. Experimental results show that AMSEA are very efficient algorithms for the estimation of motion vectors.

• Journal of the Semiconductor & Display Technology
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• v.15 no.1
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• pp.47-51
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• 2016

Human visual system infers 3D vision through stereo disparity in the stereoscopic images, and stereo visioning are recently being used in consumer electronics which has resulted in much research in the application field. Basically, stereo vision system consists of four processes, which are cost computation, cost aggregation, disparity calculation, and disparity refinement. In this paper, we present and evaluate the existing various methods, focusing on cost aggregation for stereo vision system to comparatively analyze the performance of their algorithms for a given set of resources. Experiments show that Normalized Cross Correlation and Zero-Mean Normalized Cross Correlation provide higher accuracy, however they are computationally heavy for embedded system in the real time systems. Sum of Absolute Difference and Sum of Squared Difference are more suitable selection for embedded system, but they should be required on improvement to apply to the real world system.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.589-601
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• 2016

Sea surface currents were estimated by applying the Maximum Cross Correlation (MCC), Zero-mean Sum of Absolute Distances (ZSAD), and Zero-mean Sum of Squared Distances (ZSSD) algorithms to Himawari-8/Advanced Himawari Imager (AHI) thermal infrared channel data, and the comparative analysis was performed between the results of these algorithms. The sea surface currents of the Kuroshio Current region that were retrieved using each algorithm showed similar results. The ratio of errors to the total number of estimated surface current vectors had little difference according to the algorithms, and the time required for sea surface current calculation was reduced by 24% and 18%, relative to the MCC algorithm, for the ZSAD and ZSSD algorithms, respectively. The estimated surface currents were validated against those from satellite-tracked surface drifter and altimeter data, and the accuracy evaluation of these algorithms showed results within similar ranges. In addition, the accuracy was affected by the magnitude of brightness temperature gradients and the time interval between satellite image data.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.694-696
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• 2004

With the more sophisticated abilities development of video, object motion analysis and interpretation has become the fundamental task for the computer vision understanding. For that understanding, firstly, we seek a sum of absolute difference algorithm to apply to the motion detection, which was based on the scene. Then we will focus on the moving objects representation in the scene using spatio-temporal relations. The video can be explained comprehensively from the both aspects : moving objects relations and video events intervals.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.749-752
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• 2008

Various Motion Estimation (ME) algorithms have been proposed since ME requires large computational complexity. The proposed algorithm employs Enhanced Cross Search Pattern (ECSP) using motion vector of neighbor-blocks to search the motion vector. The experimental results show that proposed algorithm reduces the search point up to 35% compared to conventional methods.