• Proceedings of the Optical Society of Korea Conference
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• 1991.07a
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• pp.55-59
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• 1991

신경회로망은 뒤뇌의 신경조직이 갖는 병렬적이며 분산적인 정보처리 능력을 흉내낸 인공적인 회로망이다. 이러한 신경회로망을 영상인식, 음성인식, 적응제어 및 최적화등에 응용할 경우 지금까지 얻지 못하였던 우수한 여러 가지 특성을 얻을수 있음을 알려짐에 따라 신경회로망을 구체적으로 구현하고자 하는 연구가 활발히 이루어지고 있다. 본 고에서는 신경소자간의 연결세기의 변조에 의한 학습 원리를 설명하고 광전기적인 그현방법에 대해서 몇 개의 예를 들어 설명하고 그 발전 가능성에 대하여 기술하였다.

• Defense and Technology
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• no.2 s.288
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• pp.50-59
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• 2003

전술$C^4I$체계가 전력화되어 작전반응이 더욱 빨라지고 획득한 정보가 필요한 부서와 제대에 모두 공유되고, 부대의 각종 자산을 충분히 활용 가능하며, 전장상황의 인식이 더욱 용이해지게 된다. 또한 전술$C^4I$체계 구축을 통해 미래 지상전장 운용개념인 "다차원 동시 통합전투"가 비로소 가능해진다. 이런 직접적인 효과 이외에도 군의 과학화 마인드를 확산시키며, 민간의 선진기술이 군에 적용되는 간접적인 효과가 있을 것이다. 우리 군이 현재 미래 전장환경과 주변국 위협에 대비하여 장거리 타격수단에 표적을 제공하기 위한 대부대용 UAV를 전력화하여 전천후 감시로 실시간 장거리 영상정보를 수집하고 있는 것은 획기적인 사실이다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.520-522
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• 2001

얼굴영역 및 얼굴구성요소 추출은 얼굴을 구별하고 인식하거나 얼굴 데이터베이스로부터 원하는 얼굴을 검색하기 위하여 필요한 기술로 다양한 방법들이 연구되어 왔다. 본 연구에서는 배경이 복잡한 칼라 얼굴영상에서 워터쉐드와 동적 피부색 범위로 얼굴후보영역을 선택한 후 각 영역내의 소영역들에 대한 칼라특성과 대칭정보를 분석하여 얼굴영역과 비얼굴 영역을 구분함으로써 얼굴영역 및 얼굴구성요소를 추출하는 방법을 제안한다. 제안된 방법이 기존연구에 비해 피부색 배경영역에 의한 오류를 제거하고 정확성이 우수한 점을 실험결과롤 제시하고 분석한다.

• Journal of Korea Water Resources Association
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• v.48 no.2
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• pp.79-90
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• 2015

In this study, the water quality parameters of Geum-river were estimated using Landsat 8 satellite image data which had launched in March 2013. The goal of this research is to predict HAB and to monitor spatial pattern of total nitrogen (TN) and total phosphorus (TP) because both TN and TP are the dominant factors of the growth of harmful algal blooms (HABs). To investigate the relationship between satellite band reflectance and in situ measurement value, Pearson' correlation coefficient analysis was used. The band2, 3, 4 and 5 reflectance values among 11 bands of Landsat 8 were used which was highly associated with detecting TN and TP. The 20 in situ data set with satellite's overpass time were identified. TN showed positive relation with band 2 (0.48), band3 (0.62), band4 (0.57) at a significance level of p<0.05. TP also showed high correlation for band2 (0.59), band3 (0.59), band4 (0.58) at a significance level of p<0.01. The optimal regression equation models were constructed for TN and TP based on multiple regression equations. The estimated concentration based on derived regression equations of TN and TP were compared with in situ measurement data. Finally, the spatial pattern of the two parameters was able be monitored through mapping on November 12, 2013 and April 21, 2014.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.481-484
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• 2005

Inherent opportunities on research for restoring high resolution image from low resolution images are increasing in these days. Super resolution image reconstruction is the process of combining multiple low resolution images to form a higher resolution one. To achieve super resolution reconstruction, proper observation model which is based on subpixel shift information is required. In this context, the importance of the subpixel registration cannot be estimated because subpixel shift information cannot be obtained from original image. This paper presents a regularized adaptive super resolution reconstruction method based on phase correlated subpixel registration, where the Constrained Least Squares(CLS) Restoration is adopted as a post process.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.293-294
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• 2019

본 논문에서는 전기차 파생 IT융합 서비스의 일환으로 원활한 전기차 충전을 지원하기 위한 불법 주차 방지 시스템을 제안한다. 국내 전기차 관련 법에 따르면 전기차 충전소 앞에 전기차가 아닌 일반 차량이 불법으로 주차를 하게 되면 과태료를 내게 되어 있다. 따라서, 제안한 시스템에서는 전기차가 아닌 일반차가 주차를 하면 경광등 작동시켜 운전자에게 경고한다. 제안한 시스템에서는 딥러닝 기반의 영상인식 SW를 적용하였다. 다양한 조도 환경에서 인식 성공률을 분석하였고 어두운 저녁에는 주변 광량에 따라 인식이 잘 이뤄지지 않는 것을 확인하였다. 향후 추가 LED를 더해 광량의 부족함에 따른 인식률 저하를 개선하는 연구를 진행할 계획이다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.73-80
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• 2012

Recent research efforts have focused on combining high dynamic range imaging with super-resolution reconstruction to enhance both the intensity range and resolution of images. The processes developed to date start with a set of multiple-exposure input images with low dynamic range (LDR) and low resolution (LR), and require several procedural steps: conversion from LDR to HDR, SR reconstruction, and tone mapping. Input images captured with irregular exposure steps have an impact on the quality of the output images from this process. In this paper, we present a simplified framework to replace the separate procedures of previous methods that is also robust to different sets of input images. The proposed method first calculates weight maps to determine the best visible parts of the input images. The weight maps are then applied directly to SR reconstruction, and the best visible parts for the dark and highlighted areas of each input image are preserved without LDR-to-HDR conversion, resulting in high dynamic range. A new luminance control factor (LCF) is used during SR reconstruction to adjust the luminance of input images captured during irregular exposure steps and ensure acceptable luminance of the resulting output images. Experimental results show that the proposed method produces SR images of HDR quality with luminance compensation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.907-910
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• 2011

This paper proposes a character segmentation algorithm of steel plate images composed of adaptive binarization by the SCW (Sliding Concentric Windows) technique, the object labelling by CCA (Connected Component Analysis), and 2D projection method. The SCW technique carries out the grayscale-to-binary image conversion in consideration of local characteristics of images. The character decision algorithm followed by the labelling technique by CCA (Connected Component Analysis) determines the character area effectively reducing the noise effect. The 2D projection with horizontal and vertical directions produces a tight bounding box for a character based on the cross points. Experimental results indicate that the proposed algorithm segments the characters in steel plate images effectively. The proposed algorithm can be applied to the devices with limited resources due to its excellent performance and low complexity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.115-117
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• 2021

Currently, as IoT technology develops, monitoring systems are being used in various fields, and image processing is being used in various forms. Image data causes noise due to various causes during the transmission and reception process, and if it is not removed, loss of image information or error propagation occurs. Therefore, denoising images is essential. Typical methods of eliminating Salt and Pepper noise in images include AF, MF, and A-TMF. However, existing methods have the disadvantage of being somewhat inadequate in high-density noise. Therefore, in this paper, we propose an algorithm for determining noise for Salt and Pepper denoising and replacing the central pixel with an original pixel if it is non-noise, and processing the filtering mask by segmenting and averaging it in eight directions. We evaluate the performance by comparing and analyzing the proposed algorithms with existing methods.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.1 s.24
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• pp.51-59
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• 2003

This study intended to extract the spatial data and attribute data from the images of terrestrial and aerial photographs and to compile the digital map from the images using various kinds of photogrammetric analysis. The Three Dimensional Frame Model (3DFM) was produced from multiple images of terrestial photographs, and the Three Dimensional Photo Image Model (3DPIM) was made using 3DFM and image patches of terrestrial photo, which is useful for identifying the feature and characteristics of the object. In addition, the spatial data base for the buildings, roads and supplementary facilities in the objective area was updated by the vectorizing procedures with small scale areal photos.