• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.10
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• pp.933-939
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• 2012

In general, the three-dimensional(3D) coordinates of the manufactured ship blocks are measured using the laser measuring equipment by ship engineers. But, many deflections between the measured coordinates in manufactured step and the designed coordinates in the design step are occurred because of the measuring process of ship blocks manually. Thus, the ship engineer should conform the consistency between the measured coordinates and the designed coordinates step by step, and it largely causes the loss of manpower and time. In this paper, the automated pattern matching algorithm of 3D coordinates for quality control in ship blocks is suggested in order to solve this problem, and the performance of the algorithm is analyzed using the 3D coordinates simulation software developed by our research laboratory. The coordinates matching rate of the measured coordinates in the single/multi ship block(s) is about 90.2% under the tolerated distance error range is 20~25cm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1792-1801
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• 2003

In these days, image mosaic is getting interest in the field of advertisement, tourism, game, medical imaging, and so on with the development of internet technology and the performance of personal computers. The main problem of mage mosaic is searching corresponding points correctly in the overlapped area between images. However, previous methods requires a lot of CPU times and data processing for finding corresponding points. And they need repeated recording with a revolution of 360 degree around objects or background. This paper presents a new image mosaic method which generates a panorama image from a video sequence recorded by a general video camera. Our method finds the corresponding points between two successive images by using a new direction oriented 3­step block matching methods. Experimental results show that the suggested method is more efficient than the methods based on existing block matching algorithm, such as full search and K­step search algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.6A
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• pp.1107-1116
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• 2001

고속 IP 주소 룩업(lookup)은 고속 인터넷 라우터의 성능을 좌우하는 주요 요소이다. LPM(longest prefix matching) 탐색은 IP 주소 룩업에서 가장 시간이 많이 걸리는 부분이다. PICAM은 고속 LPM 탐색을 위한 파이프라인 CAM 구조로서, 기존 CAM(content addressable memory, 내용 주수화 메모리)을 이용한 방법보다 룩업 테이블의 갱신속도가 빠르면서도 LPM 탐색율이 높은 CAM 구조이다. PICAM은 3단계의 파이프라인으로 구성된다. 단계 1 및 단계 2의 키필드분할수 및 매칭점의 분포에 따라 파이프라인의 성능이 좌우되며, LPM 탐색율이 달라질 수 있다. 본 논문에서는 PICAM의 파이프라인 성능모델을 제시하고, 이산사건 시뮬레이션(discrete event simulation)을 수행하여, 최적의 PICAM 구조를 도출하였다. IP version 4인 경우 키필드분할수를 8로 하고, 부하가 많이 걸리는 키필드블록을 중복 설치하는 것이 최적구조이며, IP version 6인 경우 키필드블록의 개수를 16으로 하는 것이 최적구조다.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.2
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• pp.67-74
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• 2013

Approximate string matching problems have been studied in diverse fields. Recently, fast approximate string matching algorithms are being used to reduce the time and costs for the next generation sequencing. To measure the amounts of errors between two strings, we use a distance function such as the edit distance. Given two strings X(|X| = m) and Y(|Y| = n) over an alphabet ${\Sigma}$, the edit distance between X and Y is the minimum number of edit operations to convert X into Y. The edit distance between X and Y can be computed using the well-known dynamic programming technique in O(mn) time and space. The edit distance also can be computed using the Four-Russians' algorithm whose preprocessing step runs in $O((3{\mid}{\Sigma}{\mid})^{2t}t^2)$ time and $O((3{\mid}{\Sigma}{\mid})^{2t}t)$ space and the computation step runs in O(mn/t) time and O(mn) space where t represents the size of the block. In this paper, we present a parallelized version of the computation step of the Four-Russians' algorithm. Our algorithm computes the edit distance between X and Y in O(m+n) time using m/t threads. Then we implemented both the sequential version and our parallelized version of the Four-Russians' algorithm using CUDA to compare the execution times. When t = 1 and t = 2, our algorithm runs about 10 times and 3 times faster than the sequential algorithm, respectively.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.494-503
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• 2011

In this paper, we propose a recognition application of facial expression for laughter theraphy on smartphone. It detects face region by using AdaBoost face detection algorithm from the front camera image of a smartphone. After detecting the face image, it detects the lip region from the detected face image. From the next frame, it doesn't detect the face image but tracks the lip region which were detected in the previous frame by using the three step block matching algorithm. The size of the detected lip image varies according to the distance between camera and user. So, it scales the detected lip image with a fixed size. After that, it minimizes the effect of illumination variation by applying the bilateral symmetry and histogram matching illumination normalization. After that, it computes lip eigen vector by using PCA(Principal Component Analysis) and recognizes laughter expression by using a multilayer perceptron artificial network. The experiment results show that the proposed method could deal with 16.7 frame/s and the proposed illumination normalization method could reduce the variations of illumination better than the existing methods for better recognition performance.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.359-368
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• 2002

In this paper, we propose effective boundary line extraction algorithm for moving objects by matching error image and moving vectors, and fast tracking algorithm for moving object by partial boundary lines. We extracted boundary line for moving object by generating seeds with probability distribution function based on Watershed algorithm, and by extracting boundary line for moving objects through extending seeds, and then by using moving vectors. We processed tracking algorithm for moving object by using a part of boundary lines as features. We set up a part of every-direction boundary line for moving object as the initial feature vectors for moving objects. Then, we tracked moving object within current frames by using feature vector for the previous frames. As the result of the simulation for tracking moving object on the real images, we found that tracking processing of the proposed algorithm was simple due to tracking boundary line only for moving object as a feature, in contrast to the traditional tracking algorithm for active contour line that have varying processing cost with the length of boundary line. The operations was reduced about 39% as contrasted with the full search BMA. Tracking error was less than 4 pixel when the feature vector was $(15\times{5)}$ through the information of every-direction boundary line. The proposed algorithm just needed 200 times of search operation.