• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1424-1430
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• 2020

In this paper, we propose an algorithm to remove AWGN by considering the characteristics of noise present in the image. The proposed algorithm uses block matching to calculate the output, and calculates an estimate by determining the similarity between the center mask and the matching mask. The output of the filter is calculated by adding or subtracting the estimated value and the input pixel value, and weighting is given according to the standard deviation of the center mask and the noise constant to obtain the final output. In order to evaluate the proposed algorithm, the simulation was performed in comparison with the existing methods, and analyzed through the enlarged image and PSNR comparison. The proposed algorithm minimizes the effect of noise, preserves important characteristics of the image, and shows the performance of removing noise efficiently.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.63-68
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• 1998

We present a fast adaptive block matching algorithm using characteristic of the motion vector distribution. In the presented method, the block is classified into one of four motion categories: stationary block, quasi-stationary block, medium-motion block or high-motion block according to characteristic of the MAD(0,0) distribution for motion vector, each block estiamtes the motion vector adaptively. By the simulation, the PSNR of our algorithm is similar to NTSS method. The computation amount of the presented method decreased 30.44% ~ 40.27% more than NTSS method.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.5
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• pp.314-322
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• 2022

During the shipbuilding process, many blocks are moved between shipyard workshops by block carrying vehicles called a transporter. Because block logistics management is one of the essential factors in enhancing productivity, it is necessary to manage block information with the transporter that moves it. Currently, because a large amount of data per day are collected from sensors attached to blocks and transporters via IoT infrastructure installed in shipyards, automated methods are needed to analyze them. Therefore, in this study, we developed an algorithm that can automatically match the transporter and the working block based on the GPS sensor data. By comparing the distance between the transporter and the blocks calculated from the Haversine formula, the block is found which is moved by the transporter. In this process, since the time of the measured data of moving objects is different, the time standard for calculating the distance must be determined. The developed algorithm was verified using actual data provided by the shipyard, and the correct result was confirmed with the distance based on the moving time of the transporter.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.43-46
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• 2000

In this paper, we propose a fast adaptive diamond search algorithm(FADS) for block matching motion estimation. Fast motion estimation algorithms reduce the computational complexity by using the UESA (Unimodal Error Search Assumption) that the matching error monotonically increases as the search moves away from the global minimum error. Recently many fast BMAs(Block Matching Algorithms) make use of the fact that the global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the adjacent blocks. We change the origin of search window according to the spatially adjacent motion vectors and their MAE(Mean Absolute Error). The computer simulation shows that the proposed algorithm has almost the same computational complexity with UCBDS(Unrestricted Center-Biased Diamond Search)〔1〕, but enhance PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS(Full Search), even for the large motion case, with half the computational load.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.4
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• pp.327-332
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• 2002

The main problems of computational complexity in object tracking are definition of objects, segmentations and identifications in non-structured environments with erratic movements and collisions of objects. The object's information as a region that corresponds to objects without discriminating among objects are considered. This paper describes the algorithm that, automatically and efficiently, recognizes and keeps tracks of interest-regions selected by users in video or camera image sequences. The block-based feature matching method is used for the region tracking. This matching process considers only dominant feature points such as corners and curved-edges without requiring a pre-defined model of objects. Experimental results show that the proposed method provides above 96% precision for correct region matching and real-time process even when the objects undergo scaling and 3-dimen-sional movements In successive image sequences.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.144-149
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• 1998

This paper presents a fast motion estimation algorithm, 5DS, useful for video coding. We first try block matching to 4 directions(N, E, W, S) to estimate motions in this algorith, since most of motions in video are oriented to those direction, and then try one additional diagonal matching between the matching ponts having small MADs. It makesthis algorithm possible for searching through a diagonal direction which is not adequate to logarithmic (LOG) search algorithm. This proposed algorithm has almost same PSNR but, 1.9, 1.2 times faster than classical block matching methods such as three steps search(TSS) and LOG search algorithms.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.174-177
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• 2009

In object tracking, the template matching methods have been developed and frequently used. It is fast enough, but not robust to an object with the variation of size and shape. In order to overcome the limitation of the template matching method, this paper proposes a template update technique. After finding an object position using the correlation-based adaptive predictive search, the proposed method selects blocks which contain object's boundary. It estimates the motion of boundary using block matching, and then updates template. We applied it to IR image sequences including an approaching object. From the experimental results, the proposed method showed successful performance to track object.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1189-1199
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• 2003

This paper presents a new method for the motion detection of vehicles using hierarchical motion estimation and parallel processing. It captures the road image by using a CMOS sensor. It divides the captured image into small blocks and detects the motion of each block by using a block-matching method which is based on a hierarchical motion estimation and parallel processing for the real-time processing. The parallelism is achieved by using tile pipeline and the data flow technique. The proposed method has been implemented by using an embedded system. The proposed block matching algorithm has been implemented on PLDs(Programmable Logic Device) and clustering algorithm has been implemented by ARM processor. Experimental results show that the proposed system detects the motion of vehicles in real-time.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.5
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• pp.34-42
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• 2002

In this paper, we designed the VLSI array architecture for the high speed processing of the motion estimation used by block matching algorithm. We derived the one dimensional systolic array from the full search block matching algorithm. The data and control signals of the proposed systolic array are passed through adjacent processing element. So proposed architecture has temporal and spatial locality. The I/O ports exists only in the first and last processing elements of the array. This architecture has low pin counts and modular expandability. So the proposed array architecture can be cascaded for different block size and search range.