• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06b
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• pp.115-120
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• 1999

본 논문에서는 연속적인 입력화상에서 움직임을 나타내는 객체(Object)를 적은 연산량을 사용하여 추출해 내는 알고리즘을 소개한다. 본 알고리즘은 두 가지 단계로 이루어진다. 첫번째 단계로, 이전의 영상과 현재의 영상을 비교하여 움직임의 변화를 보이는 영역을 찾는다. 이 단계에서는 영상을 비교하여 움직임을 추출하기 위하여 창조영상과 현재의 영상, 그리고 영상의 데이터로서 edge정보를 사용한다. 두 번째 단계에서는, 첫번째 단계에서 움직임으로 판단된 Object mask(변화를 가지는 영역)를 가지고 background 제거 및 Object의 정확한 shape을 만들기 위한 post-processing과정을 가지게 된다. 이 두 단계를 거친 후 입력영상에서 background를 떼어낸 최종적인 Object의 shape정보가 추출되게 된다. 이 알고리즘은 object를 기반으로 부호화함으로써 데이터의 압축률을 극대화 시키는 MPEG-4뿐만 아니라, video database, 무선 통신등과 같은 다양한 범위의 application에 적절하게 사용될 수 있을 것이다.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.202-210
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• 2019

The obstacles modeling is a fundamental and significant issue for path planning and automatic navigation of Unmanned Surface Vehicle (USV). In this study, we propose a novel obstacles modeling method based on high resolution satellite images. It involves two main steps: extraction of obstacle features and construction of convex hulls. To extract the obstacle features, a series of operations such as sea-land segmentation, obstacles details enhancement, and morphological transformations are applied. Furthermore, an efficient algorithm is proposed to mask the obstacles into convex hulls, which mainly includes the cluster analysis of obstacles area and the determination rules of edge points. Experimental results demonstrate that the models achieved by the proposed method and the manual have high similarity. As an application, the model is used to find the optimal path for USV. The study shows that the obstacles modeling method is feasible, and it can be applied to USV path planning.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.6
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• pp.929-935
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• 1986

In this paper, we describe the physical modelling and numerical aspects of a program called PRECISE(Program for Efficient Calculation of Impurity Profile in Semiconductor by Elimination) which calcualtes a two-dimensional impurity profile in silicon due to diffusion and ion implantation steps. The PRECISE enables rapid prediction of the two-dimensional impurity profile near the mask edge-or the bird's beak during the local oxidation process. This has been developed by modifying the existing one-dimentional simulator, DIFSIM(DIFfusion SIMulator to include models for arsenic diffusion and emitter dip effect which were found out to agree fairly well with the xperimental data.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.80-82
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• 2007

외곽 검출을 통한 스테레오 비전의 실시간 거리 측정을 제안하였다. 주차 시스템이나 이동 로봇의 경로 설정에 있어 실시간으로 거리 측정이 중요시 되고, 이를 해결하기 위하여 인간의 시각에 가까운 평행 축 상의 두 대의 카메라에서 취득된 영상을 이용한다. 카메라에서 얻은 영상으로부터 외곽을 추출하기 위해 Sobel Mask를 사용하였으며, 좌 우 구분을 위해 색 변환과 영상 정보로부터 거리를 측정하기 위해 영상 등록 과정을 거치고 거리 측정을 하였다. 거리 측정의 결과 2.4%의 오차율을 보였으며 이는 로봇의 이동 간에 적용할 경우 양호한 결과를 얻을 수 있을 것이다.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.510-521
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• 2001

Image retrieval system should be construct for searching fast, efficient image be extract the accurate feature information of image with more massive and more complex characteristics. Image retrieval system are essential differences between image databases and traditional databases. These differences lead to interesting new issues in searching of image, data modeling. So, cause us to consider new generation method of database, efficient retrieval method of image. In this paper, To extract feature information of edge using in searching from input image, we was performed to extract the edge by convolution Laplacian mask and input image, and we implemented the annotation-based and content-based image retrieval system for searching fast, efficient image by generation image database from extracting feature information of edge and metadata. We can improve the performance of the image contents retrieval, because the annotation-based and content-based image retrieval system is using image index which is made up of the content-based edge feature extract information represented in the low level of image and annotation-based edge feature information represented in the high level of image. As a conclusion, image retrieval system proposed in this paper is possible the accurate management of the accumulated information for the image contents and the information sharing and reuse of image because the proposed method do construct the image database by metadata.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.115-125
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• 2019

In this paper, the image is received from the camera and the lane is sensed. There are various ways to detect lanes. Generally, the method of detecting edges uses a lot of the Sobel edge detection and the Canny edge detection. The minimum use of multiplication and division is used when designing for the hardware configuration. The images are tested using a black box image mounted on the vehicle. Because the top of the image of the used the black box is mostly background, the calculation process is excluded. Also, to speed up, YCbCr is calculated from the image and only the data for the desired color, white and yellow lane, is obtained to detect the lane. The median filter is used to remove noise from images. Intermediate filters excel at noise rejection, but they generally take a long time to compare all values. In this paper, by using addition, the time can be shortened by obtaining and using the result value of the median filter. In case of the Sobel edge detection, the speed is faster and noise sensitive compared to the Canny edge detection. These shortcomings are constructed using complementary algorithms. It also organizes and processes data into parallel processing pipelines. To reduce the size of memory, the system does not use memory to store all data at each step, but stores it using four line buffers. Three line buffers perform mask operations, and one line buffer stores new data at the same time as the operation. Through this work, memory can use six times faster the processing speed and about 33% greater quantity than other methods presented in this paper. The target operating frequency is designed so that the system operates at 50MHz. It is possible to use 2157fps for the images of 640by360 size based on the target operating frequency, 540fps for the HD images and 240fps for the Full HD images, which can be used for most images with 30fps as well as 60fps for the images with 60fps. The maximum operating frequency can be used for larger amounts of the frame processing.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.5
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• pp.137-144
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• 1989

A new algorithm is presented which efficiently reports minimum width/space violation in a geometric mask pattern. The proposed algorithm solves a sequence of range search problems by employing a plane sweep method. The algorithm runs in O(n log n) time, where n is the number of edges in a mask pattern. Since a lower bound in time conplexity for reporting all minimum width/space violations is ${\Omega}$ (n log n), this algorithm is theoretically optimal within a constant multiplicaive factor. It requires O($n^{0.5}$) space which is very efficient in practice. Moreover, this algorithm, we believe, is easy to implement and practically fast (116.7 seconds for a rectilinear region with 250000 vertices ar VAX 8650.)

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.3
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• pp.104-113
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• 2000

In this study, we propose facial image recognition based on wavelet transform and neural network. This algorithm is proposed by following processes. First, two gray level images is captured in constant illumination and, after removing input image noise using a gaussian filter, differential image is obtained between background and face input image, and this image has a process of erosion and dilation. Second, a mask is made from dilation image and background and facial image is divided by projecting the mask into face input image Then, characteristic area of square shape that consists of eyes, a nose, a mouth, eyebrows and cheeks is detected by searching the edge of divided face image. Finally, after characteristic vectors are extracted from performing discrete wavelet transform(DWT) of this characteristic area and is normalized, normalized vectors become neural network input vectors. And recognition processing is performed based on neural network learning. Simulation results show recognition rate of 100 % about learned image and 92% about unlearned image.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.2043-2052
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• 1997

The object-oriented coding technique which is one of the coding methods in very low bit rate environment is suitable for videophone image sequence. The selection of source model affect image analysis. In this paper, an image analysis method for the object-oriented coding is presented. The process is composed of changed region detection andmotion estimateion. First, we use the standard deviation of frame difference as thrreshold to extract themoving area. If thesum of gray values in mask is greater than the threshold, the center pixel of the mask is regarded as moving region. After moving is detected in changed region by edge operator, observation point is determined from moving region. The motion is estimated by 6-parameter mapping method with determined observation point. The experimantal resutls show that the proposed method can significantly improve the image quality.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.12
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• pp.109-120
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• 1998

An image segmentation approach based on the fuzzy worm searching and MIN-MAX clustering algorithm is proposed in this paper. This algorithm deals with fuzzy worm value and min-max node at a gross scene level, which investigates the edge information including fuzzy worm action and spatial relationship of the pixels as the parameters of its objective function. But the conventional segmentation methods for edge extraction generally need the mask information for the algebraic model, and take long run times at mask operation, whereas the proposed algorithm has single operation according to active searching of fuzzy worms. In addition, we also propose both genetic fuzzy worm searching and genetic min-max clustering using genetic algorithm to complete clustering and fuzzy searching on grey-histogram of image for the optimum solution, which can automatically determine the size of ranges and has both strong robust and speedy calculation. The simulation results showed that the proposed algorithm adaptively divided the quantized images in histogram region and performed single searching methods, significantly alleviating the increase of the computational load and the memory requirements.