• 한국멀티미디어학회논문지
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• 제20권6호
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• pp.845-852
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• 2017

In this paper, we propose a binarization algorithm using LVQ-Merge clustering method for fast and accurate extraction of cells from cell images. The proposed method clusters pixel data of a given image by using LVQ to remove noise and divides the result into two clusters by applying a hierarchical clustering algorithm to improve the accuracy of binarization. As a result, the execution speed is somewhat slower than that of the conventional LVQ or Otsu algorithm. However, the results of the binarization have very good quality and are almost identical to those judged by the human eye. Especially, the bigger and the more complex the image, the better the binarization quality. This suggests that the proposed method is a useful method for medical image processing field where high-resolution and huge medical images must be processed in real time. In addition, this method is possible to have many clusters instead of two cluster, so it can be used as a method to complement a hierarchical clustering algorithm.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.895-898
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• 1998

In this paper, we propose an efficient marker extraction algorithm for initial image segmentation in a bottom-up segmentation scheme. The proposed algorithm generates dense markers in visually complex areas and coarse markers in visually uniform areas. which conforms to the human perceptual system. Experimental results show that the proposed method achieves better subjective quality for fine initial image segmentation.

• Applied Microscopy
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• 제37권2호
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• pp.143-146
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• 2007

The objects of the nature have three dimensional (3-D) parameters. The 3-D profiles are embedded on the photographs and microscopic images. To understand 3-D configuration, stereo pair image with thick section is frequently employed. The perception of 3-D images is possible with the aid of stereoscopic glasses, although the expert can perceive 3-D images without the glasses. Anaglyphic stereo images are constructed by various softwares from commercial and freeware. Here we would like to present an easy anaglyphs construction method with Adobe $Photoshop^{(R)}$ based on tilting paired images from high voltage electron microscope. The anaglyphic stereo images constructed revealed the same 3-D perception with conventional stereoscopy. We could zoom in/out the anaglyph image digitally to investigate the detail configuration by real time. This method is expected to contribute to understanding complex structures 3 dimensionally.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.27-33
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• 2009

본 논문은 한 장의 영상으로부터 균일 모션 블러를 빠르게 제거하는 방법을 제시한다. 한 장의 영상으로부터 모션 블러를 제거하는 기존의 방법들은 주로 전변량(total variation)이나 자연 영상 통계(natural image statistics)를 이용하였다. 반면 본 논문이 제시하는 방법은 양방향 필터(bilateral filter)와 쇼크 필터(shock filter), 그리고 영상 그레디언트(gradient)의 조작을 통해 선명한 에지를 예측하고, 이를 통해 모션 블러를 추정한다. 본 논문이 제시하는 선명한 에지 예측 기법을 통해 적은 계산량으로 효율적으로 블러를 추정할 수 있다. 실험결과를 통해 본 논문이 제시하는 방법이 넓고 복잡하게 블러된 영상을 효과적이고 빠르게 복원할 수 있음을 볼 수 있다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.464-467
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• 2007

All image data acquisition systems for example the digital camera and digital camcorder, use the image sensor to convert the image data (light) into electronic data. These image sensors are used in satellite camera for high quality and resolution image data. There are two kinds of image sensors, the one is the CCD (charge coupled device) detector sensor and the other is the CMOS (complementary metal-oxide semiconductor) image sensor. The CCD sensor control system has more complex than the CMOS sensor control system. For the high quality image data on CCD sensor, the precise timing control signal and the several voltage sources are needed in the control system. In this paper, the comparison of the CCD with CMOS sensor, the CCD sensor characteristic, and the control system will be described.

• 전자공학회논문지
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• 제50권5호
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• pp.224-230
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• 2013

운전자 보조 시스템에서 차선 경계 검출은 매우 중요하다. 본 연구는 악조건인 환경에서 차선 경계를 검출하기 위한 강건한 방법을 제안한다. 첫 번째로 원래의 image에서 iVMD(improve Vertical Mean Distribution) Method를 이용하여 수평선을 검출하고, 수평선 하위영역 image를 결정하며, 두 번째로 Canny edge detector를 사용하여 하위 영역에서 차선 표시를 추출한다. 마지막으로, RANSAC algorithm을 이용하여 각각에 맞는 line model을 적용하기 전에, k-means clustering algorithm을 이용하여 오른쪽 왼쪽 차선을 분류 한다. 제안된 알고리즘은 변종조명, 갈라진 도로, 복잡한 차선 표시, 교통신호에 관하여 상당히 정확한 차선 검출 기능을 나타낸다. 실험결과는 제안된 방법이 악조건인 환경하에서 실시간으로 효율적인 요구 사항을 충족함을 보여준다.

• 제어로봇시스템학회논문지
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• 제12권8호
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• pp.746-751
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• 2006

In this paper, we present tracking algorithm for the indoor moving object. We research passive method using a camera and image processing. It had been researched to use dynamic based estimators, such as Kalman Filter, Extended Kalman Filter and Particle Filter for tracking moving object. These algorithm have a good performance on real-time tracking, but they have a limit. If the shape of object is changed or object is located on complex background, they will fail to track them. This problem will need the complicated image processing algorithm. Finally, a large algorithm is made from integration of dynamic based estimator and image processing algorithm. For eliminating this inefficiency problem, image based estimator, Mean-shift Algorithm is suggested. This algorithm is implemented by color histogram. In other words, it decide coordinate of object's center from using probability density of histogram in image. Although shape is changed, this is not disturbed by complex background and can track object. This paper shows the results in real camera system, and decides 3D coordinate using the data from mean-shift algorithm and relationship of real frame and camera frame.

• 한국멀티미디어학회논문지
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• 제25권4호
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• pp.583-599
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• 2022

Although the object detection accuracy with a single image has been significantly improved with the advance of deep learning techniques, the detection accuracy for pig monitoring is challenged by occlusion problems due to a complex structure of a pig room such as food facility. These detection difficulties with a single image can be mitigated by using a video data. In this research, we propose a method in pig detection for video monitoring environment with a static camera. That is, by using both image processing and deep learning techniques, we can recognize a complex structure of a pig room and this information of the pig room can be utilized for improving the detection accuracy of pigs in the monitored pig room. Furthermore, we reduce the execution time overhead by applying a pruning technique for real-time video monitoring on an embedded board. Based on the experiment results with a video data set obtained from a commercial pig farm, we confirmed that the pigs could be detected more accurately in real-time, even on an embedded board.

• 대한기계학회논문집A
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• 제31권12호
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• pp.1200-1207
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• 2007

An experimental test is presented for photoelastic stress analysis around a crack tip in tensile loaded plate. The hybrid method coupling photoelastsic fringe inputs calculated by finite element method and complex variable formulations involving conformal mappings and analytical continuity is used to calculate full-field stress around the crack tip in uniaxially loaded, finite width tensile plate. In order to accurately compare calculated fringes with experimental ones, both actual and regenerated photoelastic fringe patterns are two times multiplied and sharpened by digital image processing. Regenerated fringes by hybrid method are quite comparable to actual fringes. The experimental results indicate that Mode I stress intensity factor analyzed by the hybrid method are accurate within three percent compared with ones obtained by empirical equation and finite element analysis.

• 대한전자공학회논문지TC
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• 제37권11호
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• pp.23-31
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• 2000

평면형 구조에서 공간영역 그린함수를 구하기 위해서는 무한 Sommerfeld 적분을 계산하여야 한다. 무한 적분을 짧은 시간에 계산하기 위한 복소 영상법(complex image method)과 2단계 근사화법(two-level method)은 전원점과 관측점 사이의 거리가 가까운 경우에는 정확하지만, 거리가 멀어지면 오차가 커지게 된 다. 본 논문에서는 실수축 상의 적분경로에서 파수영역 그린함수를 근사화 함으로써 코플래너 도파로 구조에서 기존의 결과에 비해 정확한 closed-form 그린함수를 구하는 방법을 제시하였다.