• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.377-382
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• 2006

In this paper, two methods based on the use of morphology and pattern matching prior to detect classified defects automatically on the back light unit which is a part of display equipments are proposed. One is the template check method which detects small size defects by using closing and opening method, and the other is the block matching method which detects big size defects by comparing with four regions of uniform blocks. The TC algorithm also can detect defects on the non-uniform pattern of BLU by using revised Otsu method. The proposed method has been implemented on the automatic defect detection system we developed and has been tested image data of BLU captured by the system.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.185-190
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• 2010

In this paper we propose the CBIR algorithm which is based on a novel image block method that combined both color and edge feature. The main drawback of global histogram representation is dependent of the color without spatial or shape information, a new image block method that divided the image to 8 related blocks which contained more information of the image is utilized to extract image feature. Based on these 8 blocks, histogram equalization and edge detection techniques are also used for image retrieval. The experimental results show that the proposed image block method has better ability of characterizing the image contents than traditional block method and can perform the retrieval system efficiently.

• Journal of the Korean Society of Industry Convergence
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• v.3 no.4
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• pp.369-378
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• 2000

Conventional fractal image compression methods have many problems in searching time for matching domain block. Proposed method is an improved method of Fisher's Quadtree Decomposition in terms of time, compression ratio, and PSNR. This method determines range block in advance using QR algorithm. First, input image is partitioned to $4{\times}4$ range block and then recomposition is performed from bottom level to specified level. As a result, this proposed method achieves high encoding and decoding speed, high compression ratio, and high PSNR than Fisher's Quadtree Decomposition method.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.96-101
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• 2001

The development of a new experimental method is required to easily observe the growth behavior of fatigue cracks. To satisfy the requirement, an image processing technique was introduced to fatigue testing. The length of surface fatigue crack could be successfully measured by the image processing system. At first, the image data of cracks were stored into the computer while the cyclic loading was interrupted. After testing, crack length was determined using image processing software which was developed by ourselves. Block matching method was applied to the detection of surface fatigue cracks. By comparing the data measured by image processing system with the data measured by manual measurement with a microscope, the effectiveness of the image processing system was established. If the proposed method is used to monitor and observe the crack growth behavior automatically, the time and efforts for fatigue test could be dramatically reduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5063-5073
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• 2016

In this paper, an efficient texture compression method is proposed for fast rendering, which exploits the spatial correlation among blocks through intra-picture block matching. Texture mapping is widely used to enhance the visual quality of results in real-time rendering applications. For fast texture mapping, it is necessary to identify an effective trade-off between compression efficiency and computational complexity. The conventional compression methods utilized for image processing (e.g., JPEG) provide high compression efficiency while resulting in high complexity. Thus, low complexity methods, such as ETC1, are often used in real-time rendering applications. Although these methods can achieve low complexity, the compression efficiency is still lower than that of JPEG. To solve this problem, we propose a texture compression method by reducing the spatial redundancy between blocks in order to achieve the better compression performance than ETC1 while maintaining complexity that is lower than that of JPEG. Experimental results show that the proposed method achieves better compression efficiency than ETC1, and the decoding time is significantly reduced compared to JPEG while similar to ETC1.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1C
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• pp.9-15
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• 2007

We propose the fast full search algorithm that reduces the computation of the block matching algorithm which is used for motion estimation of the video coding. Since the conventional spiral search method starts searching at the center of the search window and then moves search point to estimate the motion vector pixel by pixel, it is good for the slow motion pictures. However the proposed method is good for the fast and slow motion because it estimates the motion in the new search order after partitioning the search window. Also, when finding the motion vector, this paper presents the method that reduces the complexity by computing the matching error in the order which is determined by local image complexity. The proposed algorithm reduces the computation up to 99% for block matching error compared with the conventional spiral full search algorithm without any loss of image quality.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.295-296
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• 2008

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.681-684
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• 2008

We proposed a method to improve moving object detection capability of Gaussian Mixture Model by suggesting shape adaptive bidirectional block matching algorithm. This method achieves more accurate detection and tracking performance at various motion types such as slow, fast, and bimodal motions than that of Gaussian Mixture Model. Experimental results showed that the proposed method outperformed the conventional methods.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.410-421
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• 2019

Distributed compressed sensing (DCS) states that we can recover the sparse signals from very few linear measurements. Various studies about DCS have been carried out recently. In many practical applications, there is no prior information except for standard sparsity on signals. The typical example is the sparse signals have block-sparse structures whose non-zero coefficients occurring in clusters, while the cluster pattern is usually unavailable as the prior information. To discuss this issue, a new algorithm, called backtracking-based adaptive orthogonal matching pursuit for block distributed compressed sensing (DCSBBAOMP), is proposed. In contrast to existing block methods which consider the single-channel signal reconstruction, the DCSBBAOMP resorts to the multi-channel signals reconstruction. Moreover, this algorithm is an iterative approach, which consists of forward selection and backward removal stages in each iteration. An advantage of this method is that perfect reconstruction performance can be achieved without prior information on the block-sparsity structure. Numerical experiments are provided to illustrate the desirable performance of the proposed method.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.8
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• pp.966-974
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• 1999

완전 탐색 블록 정합 알고리즘(FBMA)은 다양한 움직임 추정 알고리즘 중 최상의 움직임 추정을 할 수 있으나, 방대한 계산량이 실시간 처리의 적용에 장애 요소이다. 본 논문에서는 완전 탐색 블록 정합 알고리즘에 비해 더 낮은 계산량과 유사한 화질을 가지는 새로운 고속 움직임 추정 알고리즘을 제안한다. 제안한 방법에서는 공간적인 상관성을 이용함으로써 적절한 탐색 영역의 크기를 예측할 수 있다. 현재 블록의 움직임 추정을 위하여 이웃 블록이 가지고 있는 움직임과 탐색 영역의 크기를 이용하여 현재 블록의 탐색 영역을 적응적으로 변화시키는 방법이다. 이 예측값으로 현재 블록의 탐색 영역 크기를 결정한 후, FBMA와 같이 이 영역 안의 모든 화소점들에 대하여 현재 블록을 정합하여 움직임 벡터를 추정한다. 컴퓨터 모의 실험 결과 계산량 측면에서 제안 방법이 완전 탐색 블록 정합 알고리즘보다 50%정도 감소하였으며, PSNR 측면에서는 0.08dB에서 1.29dB 정도 감소하는 좋은 결과를 얻었다.Abstract Full search block-matching algorithm (FBMA) was shown to be able to produce the best motion compensated images among various motion estimation algorithms. However, huge computational load inhibits its applicability in real applications. A new motion estimation algorithm with lower computational complexity and good image quality when compared to the FBMA will be presented in this paper. In the proposed method, The appropriate search area can be predicted by using the temporal correlation between neighbouring blocks. For motion estimation of the current block, it is the method changing adjustably search area of current block by using motion and search area size of the neighbouring block. After deciding search area size of the current block with this predicted value, we estimate motion vector that matching current block like the FBMA for every pixel in this area. By the computer simulation the computation amount of the proposed method can be greatly decreased about 50% than that of the FBMA and the good result of the PSNR can be attained.