• Journal of information and communication convergence engineering
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• v.12 no.2
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• pp.128-134
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• 2014

In this paper, we present a graphics processing unit (GPU)-based matching technique for the purpose of fast feature matching between different images. The scale invariant feature transform algorithm developed by Lowe for various feature matching applications, such as stereo vision and object recognition, is computationally intensive. To address this problem, we propose a matching technique optimized for GPUs to perform computations in less time. We optimize GPUs for fast computation of keypoints to make our system quick and efficient. The proposed method uses a self-organizing map feature matching technique to perform efficient matching between the different images. The experiments are performed on various image sets to examine the performance of the system under varying conditions, such as image rotation, scaling, and blurring. The experimental results show that the proposed algorithm outperforms the existing feature matching methods, resulting in fast feature matching due to the optimization of the GPU.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.899-905
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• 2003

An intermediate images generation method using multi-resolution based hierarchical block matching disparity map is proposed. This method is composed of a disparity estimation, an occlusion detection and intermediate image synthesis. For the disparity estimation, which is one of the important processes in intermediate image synthesis, we use the multi-resolution based hierarchical block matching algorithm to overcome the imperfect ness of block matching algorithm. The proposed method makes disparity maps more accurate and dense by multi-resolution based hierarchical block matching, and the estimated disparity maps are used to generate intermediate images of stereo images. Generated intermediate images show 0.1∼1.4 ㏈ higher PSNR than the images obtained by block matching algorithm.

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.127-131
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• 2007

This paper presents a new matching scheme for creating a single panoramic image from a sequence of partially overlapping images of the same object or scene. This matching scheme is based directly on the searching algorithm, using a multiscale approach to the Hooke-Jeeves algorithm. Matching scheme evaluation was performed using simulated pattern images. The proposed matching scheme reveals good results and could be effectively applied to real ultrasound applications.

• International Journal of Highway Engineering
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• v.17 no.5
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• pp.75-82
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• 2015

PURPOSES : In link matching using vehicular trajectory in a car navigation system, it is technically difficult to match the location of the subject vehicle with a link on an electronic map in the vehicle on a grade separation highway segment consisting of an elevated highway and atgrade highway, because of the overlap of geometric lines of the two highways. This study was initiated to propose a link matching algorithm using the characteristics of vehicular movement of the subject vehicle. METHODS : The selected test site is the highway segment between Jeong-reung IC and Gil-eum IC where the Inner Circulation Road and Jeong-reung-ro run together. To evaluate the proposed algorithm, this study collected the raw packet data of vehicles that drove on the test site. In a simulation environment, link matching was performed using an existing algorithm as well as the proposed algorithm. RESULTS: It was clearly found that the characteristics of vehicular movements are different on the two highways. CONCLUSIONS: The proposed algorithm outperformed the existing algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.6
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• pp.1361-1369
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• 1996

Motion estimation is one of the key components for high quality video coding. In this paper, a new motion estimation scheme for MPEG-like video coder is suggested. The proposed temporally adaptive motion estimation scheme consists of five functional blocks: Temporal subband analysis (TSBA), extraction of temporal information, scene change detection (SCD), picture type replacement (PTR), and temporally adapted block matching algorithm (TABMA). Here all the functional components are based on the temporal subband analysis. In this papre, we applied the analysis part of subband decompostion to the temporal axis of moving picture sequence, newly defined the temporal activity distribution (TAD) and average TAD, and proposed the temporally adapted block matching algorithm, the scene change detection algorithm and picture type replacement algorithm which employed the results of the temporal subband analysis. A new block matching algorithm TABMA is capable of controlling the block matching area. According to the temporal activity distribution of objects, it allocates the search areas nonuniformly. The proposed SCD and PTR can prevent unavailable motion prediction for abrupt scene changes. Computer simulation results show that the proposed motion estimation scheme improve the quality of reconstructed sequence and reduces the number of block matching trials to 40% of the numbers of trials in conventional methods. The TSBA based scene change detection algorithm can detect the abruptly changed scenes in the intentionally combined sequence of this experiment without additional computations.

• 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 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 IEEK Conference
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• 2006.06a
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• pp.295-296
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• 2006

This paper implements a method that tracking the moving objects that detected by the motion detection function of the digital CCTV system. We simply implement the motion detection function of the digital CCTV system that use frame difference and thresholding. When motion is detected, the motion detection function generates two outputs. One output is the event that the motion is arised in input image frame. The other output is coordinate that motion is exists. Then, do the block matching algorithm[2] using coordinate, that motion is exists, as initial coordinate of the block matching algorithm. The best matched coordinate is new initial coordinate of the block matching algorithm for the next image frame. We simply use the block matching algorithm that implements tracking the moving objects. It is simple, but useful the actual digital CCTV system.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.859-863
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• 1993

There are two methods to get 3-dimensional information by matching image pair feature-based matching and area-based matching. One of the problems in the area-based matching is how the optimal search region which gives accurate correlation between given point and its neighbors can be selected. In this paper, we proposed a new area-based matching algorithm which uses edge-features used in the conventional feature-based matching. It first selects matching candidates by feature-based and matches image pair with area-based method by taking these candidates as guidance to decision of search area. The results show that running time is reduced by optimizing search area(considering edge points and continuity of disparity), keeping on the precision as the conventional area-based matching method.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1343-1358
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• 2020

In the stagewise arithmetic orthogonal matching pursuit algorithm, the weak threshold used in sparsity estimation is determined via maximum iterations. Different maximum iterations correspond to different thresholds and affect the performance of the algorithm. To solve this problem, we propose an improved variable weak threshold based on the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the residual error value to control the weak threshold. When the residual value decreases, the threshold value continuously increases, so that the atoms contained in the atomic set are closer to the real sparsity value, making it possible to improve the reconstruction accuracy. In addition, we improved the generalized Jaccard coefficient in order to replace the inner product method that is used in the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the covariance to replace the joint expectation for two variables based on the generalized Jaccard coefficient. The improved generalized Jaccard coefficient can be used to generate a more accurate calculation of the correlation between the measurement matrixes. In addition, the residual is more accurate, which can reduce the possibility of selecting the wrong atoms. We demonstrate using simulations that the proposed algorithm produces a better reconstruction result in the reconstruction of a one-dimensional signal and two-dimensional image signal.