• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.263-265
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• 2003

The computation cost of image registration is affected by searching data size and space. This paper proposes an efficient image registration algorithm that uses multi-resolution wavelet decomposed image to reduce the data size search. The algorithm determines the correlation detection at low resolution on low-pass sub bands of wavelet and generate mask for higher resolution as part of a coarse to fine registration algorithm. The correlation matching is defined for coarse resolution similarity measurement, while mutual information (MI) is used at fine resolution. The results show that the new efficient mask-based algorithm improves computational efficiency and yields robust and consistent image registration results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.275-284
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• 2023

Land monitoring involves systematically understanding changes in land use, leveraging spatial information such as satellite imagery and aerial photographs. Recently, the integration of deep learning technologies, notably object detection and semantic segmentation, into land monitoring has spurred active research. This study developed a web service to facilitate such integrations, allowing users to analyze aerial and drone images using CNN models. The web service architecture comprises AI, WEB/WAS, and DB servers and employs three primary deep learning models: DeepLab V3, YOLO, and Rotated Mask R-CNN. Specifically, YOLO offers rapid detection capabilities, Rotated Mask R-CNN excels in detecting rotated objects, while DeepLab V3 provides pixel-wise image classification. The performance of these models fluctuates depending on the quantity and quality of the training data. Anticipated to be integrated into the LX Corporation's operational network and the Land-XI system, this service is expected to enhance the accuracy and efficiency of land monitoring.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.747-752
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• 2011

The position detection of overlapping area in the interframe for image stitching using auto and cross correlation function (ACCF) and compounding one image with the stitching algorithm is presented in this paper. ACCF is used by autocorrelation to the featured area to extract the filter mask in the reference (previous) image and the comparing (current) image is used by crosscorrelation. The stitching is detected by the position of high correlation, and aligns and stitches the image in shifting the current image based on the moving vector. The ACCF technique results in a few computations and simplicity because the filter mask is given by the featuring block, and the position is enabled to detect a bit movement. Input image captured from CMOS is used to be compared with the performance between the ACCF and the window correlation. The results of ACCF show that there is no seam and distortion at the joint parts in the stitched image, and the detection performance of the moving vector is improved to 12% in comparison with the window correlation method.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.80-85
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• 2008

Images are often corrupted by noises during signal acquisition and transmission. Among those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. For different types of noise have different characters, how to remove them separately from degraded image is one of the most fundamental problems. Thus, a modified image restoration algorithm is proposed in this paper, which can not only remove impulse noise of random values, but also remove the AWGN selectively. The noise detection step is by calculating the intensity difference and the spatial distance between pixels in a mask. To divide two different noises, the method is based on three weighted parameters. And the weighted parameters in the filtering mask depend on spatial distances, positions of impulse noise and standard deviation of AWGN. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, and simulation results demonstrate that the proposed method performs better than conventional median-type filters, in preserving edge details.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.519-521
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• 2015

세라믹 소재 영상에서 결함 영역이 다른 영역보다 명암도가 밝게 나타나는 정보를 이용하여 ROI 영역을 추출한다. 추출된 ROI 영역에서 Blurring 기법을 적용하여 미세 잡음을 제거한다. 미세 잡음이 제거된 ROI 영역에서 Median Filter기법을 적용하여 임펄스 잡음을 제거한다. 임펄스 잡음이 제거된 영역에서 Prewit Mask을 적용하여 수평과 수직 에지를 검출하고 검출된 에지에 윤곽선 추적 기법을 적용하여 결함 영역의 경계를 보정한다. 보정된 영상에서 Blob Labeling 기법을 적용하여 최종적으로 결함 영역을 추출한다. 제안된 방법을 8mm와 10mm 세라믹 소재 영상을 대상으로 실험한 결과, 기존의 결함 검출 방법보다 제안된 검출 방법의 검출 성능이 개선된 것을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.4
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• pp.309-321
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• 1988

This paper proposes on the algorithm of axis equation & radius function for the G.C representation which describes the curved objects with circular cross section. Object combined with linear and nonlinear parts is detached by clustering from depth data & axis points is extracted by normal vecter of the surface mask patches. In ths case of nonlinear axis point, axis equation is described by Hermite curve & the effectiveness of this paper is demonstrated by serveral experiments.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.199-200
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• 2017

본 논문에서는 최근 황사 및 미세 먼지 등으로 늘어나는 환경적 오염으로부터 어린이들이 올바른 마스크 사용을 할 수 있도록 스마트 기능이 포함된 마스크를 제안하는 것이다. 제 4차 산업혁명으로 인하여 사물인터넷이나 스마트 제품은 날로 급증하고 있는 추세이다. 따라서, 어린이들이 많이 사용하는 마스크 제품에 스마트한 기능을 넣고자 한다. 스마트 밴드를 통해 미세먼제 오염도를 측정할 수 있고, 호흡 상태를 파악하고 분비물의 상태를 분석할 수가 있다. 따라서 의료기관을 방문하기 전까지 어린이들의 건강상태를 보다 즉각적으로 파악할 수가 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1716-1725
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• 1996

In this paper, the huffman decoder which is a part of the decoder in JPEG standard format is designed by using a new Ternary CAM. First, the 256 word * 16 bit-size new bit-word all parallel Ternary CAM system is designed and verified using SPICE and CADENCE Verilog-XL, and then the verified novel Ternary CAM is applied to the new huffman decoder architecture of JPEG. So the performnce of the designed CAM cell and it's block is verified. The new Ternary CAM has various applications because it has search data mask and storing data mask function, which enable bit-wise search and don't care state storing. When the CAM is used for huffman look-up table in huffman decoder, the CAM is partitioned according to the decoding symbol frequency. The scheme of partitioning CAM for huffman table overcomes the drawbacks of all-parallel CAM with much power and load. So operation speed and power consumption are improved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1279-1289
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• 1992

Fault-tolerant system in improved the reliability and safety by using hardware and software redundancy. Fault mask and detection, identification techniques are conditionally used with system's application areas. Here DMR system is operated with standby and fail-safe module method that has minimal hardware and software redundancy, then its reliablity and safety comparison is presented respectively. Also this paper proposed an effective methods of dealing with transient faults as compared system's MTTFs to transient faults tolerance capabilities of self-diagnosis program.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.11a
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• pp.907-910
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• 2004

본 논문에서는 자동차 번호판 인식의 성공률을 높이기 위해 자동차 번호판을 정형화하는 법을 제시한다. 번호판의 테두리 직선을 찾기 위해서 Hough 변환과 Mask 를 사용한 방법을 제시하고, 그 방법을 사용하여 다수의 기울어진 번호판 영상을 정확하게 정형화할 수 있었다. Hough 변환과 Mask 를 이용한 직선 검출 방법은 두꺼운 에지 성분이나 저해상도 영상의 경우에도 효과적으로 직선을 검출해냄을 알 수 있었다.