• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.318-324
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• 2001

In this paper we propose the adaptive scheme to place more search points as long as the operation tapability of the motion estimator in the video codec permits. And the proposed algorithm takes advantage of the intuitive fact that the quality of the decoded video is more degraded as the spatial frequency of the corresponding block is increased due to the augmentation of local minima per unit area. Thererore, we propose the scheme to enhance the quality by locating relatively more search points in the block with high frequency components by analyzing the spatial frequencies of the video sequence. As a result, the proposed scheme can adaptively place more search points possibly permitted by the motion estimator and guarantees better quality compared to the TSS and FS.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.638-648
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• 2000

This paper introduces a new technique for block is matching motion estimation. Since the temporal correlation of the image sequence, the motion vector of a block is highly related to the motion vector of the same coordinate block in the previous image frame. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous frame, the total number of search points used to find the motion vector of the current block may be reduced significantly. Using that idea, an efficient predicted direction search algorithm (PDSA) for block matching algorithm is proposed. Based on the direction of the blocks of the two successive previous frames, if the direction of the to successive blocks is same, the first search point of the proposed PDSA is moved two pixels to the direction of the block. The searching process after moving the first search point is processed according to the fixed search patterns. Otherwise, full search is performed with search area $\pm$2. Simulation results show that PSNR values are improved up to the 3.4dB as depend on the image sequences and improved about 1.5dB on an average. Search times are reduced about 20% than the other fast search algorithms. Simulation results also show that the performance of the PDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS(Full Search) algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.56-65
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• 2009

Stereoscopic images consist of the left image and the right image. Thus, stereoscopic images have much amounts of data than single image. Then an efficient image compression technique is needed, the DPCM-based predicted coding compression technique is used in most video coding standards. Motion and disparity estimation are needed to realize the predicted coding compression technique. Their performing algorithm is block matching algorithm used in most video coding standards. Full search algorithm is a base algorithm of block matching algorithm which finds an optimal block to compare the base block with every other block in the search area. This algorithm presents the best efficiency for finding optimal blocks, but it has very large computational loads. In this paper, we have proposed fast disparity estimation algorithm using motion and disparity vector information of the prior frame in stereo image coding. We can realize fast disparity vector estimation in order to reduce search area by taking advantage of global disparity vector and to decrease computational loads by limiting search points using motion vectors and disparity vectors of prior frame. Experimental results show that the proposed algorithm has better performance in the simple image sequence than complex image sequence. We conclude that the fast disparity vector estimation is possible in simple image sequences by reducing computational complexities.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.403-404
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• 2008

In this paper, a new 4-way search window is developed for H.264 Motion Estimation(ME) to improve the memory bandwidth. The proposed 4-way(up, down, left, right) search window could improve the reuse of overlapped window data to reduce the redundancy access factor by 1.4, though the 1/3-way search window requires $7.7{\sim}11$ times of data retrieval redundantly. In experiments, the new implementation of 4-way search window on Altera Stratix-III could deal with CIF ($352{\times}288$) video of 3 reference frame, $48{\times}48$ search area and $16{\times}16$ macroblock by 30fps real time at 55.2MHz.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1170-1182
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• 2004

A novel 4-way pipelined processing architecture is presented for three-step search block-matching motion estimation. For the 4-way pipelined processing, we have developed a method which divides the current block and search area into 4 subregions respectively and processes them concurrently. Also, we have developed memory partitioning method to access pixel data from 4 subregions concurrently without memory conflict. The architecture has been designed and simulated with C language and VHDL. Experimental results show that the proposed architecture achieves a high performance for real time motion estimation.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.631-632
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• 2006

In this paper, acquiring the more desirable to adopt design SoC for the fast hierarchical motion estimation, we exploit foreground and background search algorithm (FBSA) base on the dual arithmetic processor element(DAPE). It is possible to estimate the large search area motion displacement using a half of number PE in general operation methods. And the proposed architecture of MHME improve the VLSI design hardware through the proposed FBSA structure with DAPE to remove the local memory. The proposed FBSA which use bit array processing in search area can improve structure as like multiple processor array unit(MPAU).

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2001.11b
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• pp.95-98
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• 2001

본 논문에서는 동영상 압축 방식에서 압축 효율을 증가시키는 움직임 벡터 추정 방식의 개선된 방법에 대해 제안한다. 움직임 벡터 추정 방식의 하나인 BMA(block matching algorithm) 중에 가장 좋은 성능을 보이는 FSA(full search algorithm)은 움직임의 정도를 예측하지 않고 모든 블록에 대해 고정적인 탐색 영역이 결정되어 있다. 이는 계산량을 상당히 크게 하는 원인이 된다. 제안된 방식은 블록 사이의 움직임이 유사한 특성을 이용하여 블록 단위의 동적인 탐색 영역을 결정하여 계산량을 효율적으로 줄이면서 FSA와 유사한 특성을 유지하게 된다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1B
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• pp.128-140
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• 2000

In this paper, we propose a fast block matching algorithm using the mean absolute error (MAE) of neighbor search point and search region reduction. The proposed algorithm is composed of two stages. At the first stage,the search region is divided into nonoverlapped 3$\times$3 areas and MAE of the center point of each area iscalculated. The minimum MAE value of all the calculated MAE's is determined as reference MAE. At thesecond stage, because the possibility that final motion vector exist near the position of reference MAE is veryhigh, we use smaller search region than first stage, And, using the MAE of center point of each area, the lowerbound of rest search point of each area is calculated and block matching process is performed only at the searchpoints that the lower bound is smaller than reference MAE. By doing so, we can significantly reduce thecomputational complexity while keep the increasement of motion estimation error small.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3030-3038
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• 2023

Nowadays, mobile robots have been used to search for uncontrolled radioactive source in indoor environments to avoid radiation exposure for technicians. However, in the indoor environments, especially in the presence of obstacles, how to make the robots with limited sensing capabilities automatically search for the radioactive source remains a major challenge. Also, the source search efficiency of robots needs to be further improved to meet practical scenarios such as limited exploration time. This paper proposes an automatic source search strategy, abbreviated as ACA: the location of source is estimated by a convolutional neural network (CNN), and the path is planned by the A-star algorithm. First, the search area is represented as an occupancy grid map. Then, the radiation dose distribution of the radioactive source in the occupancy grid map is obtained by Monte Carlo (MC) method simulation, and multiple sets of radiation data are collected through the eight neighborhood self-avoiding random walk (ENSAW) algorithm as the radiation data set. Further, the radiation data set is fed into the designed CNN architecture to train the network model in advance. When the searcher enters the search area where the radioactive source exists, the location of source is estimated by the network model and the search path is planned by the A-star algorithm, and this process is iterated continuously until the searcher reaches the location of radioactive source. The experimental results show that the average number of radiometric measurements and the average number of moving steps of the ACA algorithm are only 2.1% and 33.2% of those of the gradient search (GS) algorithm in the indoor environment without obstacles. In the indoor environment shielded by concrete walls, the GS algorithm fails to search for the source, while the ACA algorithm successfully searches for the source with fewer moving steps and sparse radiometric data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.87-95
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• 2003

This paper proposes an object detection algorithm using the Multiresolution Motion Estimation(MRME) in wavelet d야main. A existing motion estimation method has characteristics of motion estimation but it requires having computation. Motion estimation in higher resolution used the motion vector of the lower resolution with the MRME that has parent-child relationship on wavelet coefficients. This method reduces the search area of motion estimation in higher resolution and computational complexity. The computational complexity of the proposed method is about 40% of the existing method using 3-level Set Partitioning in Hierarchical Trees(SPIHT) wavelet transform. The experimental results with the proposed method showed about 11% decrease of Mean Absolute Difference(MAD) and gains able to precise tracking of object.