• Journal of the Semiconductor & Display Technology
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• 제10권2호
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• pp.31-38
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• 2011

This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.211-230
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• 2022

In image segmentation, for the condition that objects (targets) and background in an image are intertwined or their common boundaries are vague as well as their textures are similar, and the targets in images are greatly variable, the deep learning might be difficult to use. Hence, a new method based on graph theory and guided feathering is proposed. First, it uses a guided feathering algorithm to initially separate the objects from background roughly, then, the image is separated into two different images: foreground image and background image, subsequently, the two images are segmented accurately by using the improved graph-based algorithm respectively, and finally, the two segmented images are merged together as the final segmentation result. For the graph-based new algorithm, it is improved based on MST in three main aspects: (1) the differences between the functions of intra-regional and inter-regional; (2) the function of edge weight; and (3) re-merge mechanism after segmentation in graph mapping. Compared to the traditional algorithms such as region merging, ordinary MST and thresholding, the studied algorithm has the better segmentation accuracy and effect, therefore it has the significant superiority.

• The KIPS Transactions:PartB
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• 제17B권1호
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• pp.37-46
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• 2010

In this paper we have presented a two dimensional model based tracking system using improved chamfer matching. Conventional chamfer matching could not calculate similarity well between the object and image when there is very cluttered background. Then we have improved chamfer matching to calculate similarity well even in very cluttered background with edge and corner feature points. Improved chamfer matching is used as likelihood function of particle filter which tracks the geometric object. Geometric model which uses edge and corner feature points, is a discriminant descriptor in color changes. Particle Filter is more non-linear tracking system than Kalman Filter. Then the presented method uses geometric model, particle filter and improved chamfer matching for tracking object in complex environment. In experimental result, the robustness of our system is proved by comparing other methods.

• Journal of the Korea Convergence Society
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• 제8권8호
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• pp.33-40
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• 2017

In this paper, we propose a text extraction method by pattern analysis on contour for effective text detection in image. Text extraction algorithms using edge based methods show good performance in images with simple backgrounds, The images of complex background has a poor performance shortcomings. The proposed method simplifies the color of the image by using K-means clustering in the preprocessing process to detect the character region in the image. Enhance the boundaries of the object through the High pass filter to improve the inaccuracy of the boundary of the object in the color simplification process. Then, by using the difference between the expansion and erosion of the morphology technique, the edges of the object is detected, and the character candidate region is discriminated by analyzing the pattern of the contour portion of the acquired region to remove the unnecessary region (picture, background). As a final result, we have shown that the characters included in the candidate character region are extracted by removing unnecessary regions.

• Proceedings of the Korean Vacuum Society Conference
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• 한국진공학회 1999년도 제17회 학술발표회 논문개요집
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• pp.191-191
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• 1999

Extended X-ray Absorption Fine Structure (EXAFS)는 일반적으로 널리 사용하는 X선 회절분광기로 분석하기 힘든 chemical 또는 biological system의 structural analyses에 매우 유용한 분석방법이다. 특히 세라믹이나 유전체 비정질 재료의 미세 원자 구조에 관한 정보를 얻는데는 가장 강력한 분석방법중의 하나로 알려져 있다. 현재까지 대부분의 EXAFS 실험은 방사광 가속기를 이용하여 수행하였다. 그런데 신제품 개발의 순환주기가 급속하게 단축되는 현실적인 문제에 부응하기 위하여 실험실에서 EXAFS 실험을 수행할 수 있는 system을 개발하게 되었다. 개발한 XIEES 장비는 rotating anode 형의 18kW X-ray source, Optical system, Detection system, Stepping motor control system, vacuum system, Utility 등으로 구성하였다. Optical system에서의 6개의 Johanson type monochromator를 사용하여 분석가능한 x-ray energy range를 480eV에서 41keV까지 구현하였다. 이는 산소에서 우라늄까지 분석이 가능함을 의미하는 것으로, 산화물 연구에 많이 활용할 것으로 기대한다. XIEES는 투과 및 형광 X-ray를 검출할 수 있는 기능과 X-ray에 의해 여기 되는 모든(광전자, Aiger 전자, 이차전자)들을 검출할 수 있는 기능을 갖추고 있는데 이를 Total Electron Yield 측정이라고 한다. Total Electron Yield 측정은 박막 시료와 같이 투과가 되지 않는 시료를 분석할 뿐만 아니라, 경원소 분석, 낮은 에너지에서 흡수 edge가 나타나는 L-edge 측정을 통한 전자 구조 분석 등에 유용한다. 실험실용 XIEES 장비는 방사광가속기에 비해 x-ray flux가 크게 뒤지는 문제와 Total Electron Yield를 측정하는 데 있어서 source에서 나오는 x-ray beam이 진공용기 안에서 산란되어 이차전자를 여기하고 이 이차전자들이 전자검출기에 유입되어 측정에 영향을 미치는 background 문제 등이 있다. 이 두 가지 문제를 해결하기 위하여 Capillary tube를 사용하였다. 본 연구에서는 실험실용 XIEES 장비를 소개하고 이를 이용하여 Cu standard 시료에서 측정한 EXAFS 결과와 Capillary tube를 사용하여 얻은 x-ray flux 증진 및 background 제거 효과에 대해서 발표한다.

• Journal of Digital Contents Society
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• 제17권5호
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• pp.441-448
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• 2016

In this paper, we propose a method that segments the image, extracts its slope and compensate it in the image that text and background are mixed. The proposed method uses morphology based preprocessing and extracts the edges using canny operator. And after segmenting the image which the edges are extracted, it excludes the areas which the edges are included, only uses the area which the edges are included and creates the projection histograms according to their various direction slopes. Using them, it takes a slope having the greatest edge concentrativeness of each area and compensates the slope of the scene. On extracting the slope of the mixed scene of the text and background, the method can get better results as 0.7% than the existing methods as it excludes the useless areas that the edges do not exist.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• 제7권12호
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• pp.947-954
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• 2017

In case of a fire in urban large structures such as super high-rise buildings, evacuation guidance must be provided to the occupants in order to minimize human deaths and injuries. Therefore, it is essential to provide emergency evacuation guidance when a major fire occurs. In order to effectively support evacuation guidance, it is important to identify major items such as fire location, occupant position, escape route, etc. Also, it is important to quickly identify evacuation areas where residents can safely evacuate from a fire. In this paper, we analyze the CCTV video and propose a method of measuring visibility of the evacuation zone from the smoke caused by the fire in order to determine the safety of evacuation area. To do this, we first extract the background video from the smoke video to measure the visibility of the specific area due to smoke. After generating an edge-extracted image for the extracted background video, the degree of visibility is measured by calculating the change in the edge strength due to smoke.

• The KIPS Transactions:PartB
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• 제13B권3호
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• pp.255-274
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• 2006

Moving object boundary is very important for the accurate segmentation of moving object. We extract the moving object boundary from the moving object edge. But the object boundary shows broken boundaries so we develop a novel boundary linking algorithm to link the broken boundaries. The boundary linking algorithm forms a quadrant around the terminating pixel in the broken boundaries and searches for other terminating pixels to link in concentric circles clockwise within a search radius in the forward direction. The boundary linking algorithm guarantees the shortest distance linking. We register the background from the image sequence using the stationary background filtering. We construct two object masks, one object mask from the boundary linking and the other object mask from the initial moving object, and use these two complementary object masks to segment the moving objects. The main contribution of the proposed algorithms is the development of the novel object boundary linking algorithm for the accurate segmentation. We achieve the accurate segmentation of moving object, the segmentation of multiple moving objects, the segmentation of the object which has a hole within the object, the segmentation of thin objects, and the segmentation of moving objects in the complex background using the novel object boundary linking and the background automatically. We experiment the algorithms using standard MPEG-4 test video sequences and real video sequences of indoor and outdoor environments. The proposed algorithms are efficient and can process 70.20 QCIF frames per second and 19.7 CIF frames per second on the average on a Pentium-IV 3.4GHz personal computer for real-time object-based processing.

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제48권6호
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• pp.105-114
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• 2011

The snake algorithm is widely adopted to track objects by extracting the active contour of the object from background. However, it fails to track the target converging to the background if there exists background whose gradient is greater than that of the pixels on the contour. Also, the contour may shrink when the target moves fast and the snake algorithm misses the boundary of the object in its searching window. To alleviate these problems, we propose an improved algorithm that can track object contour more robustly. Firstly, we propose two external energy functions, the edge energy and the contrast energy. One is designed to give more weight to the gradient on the boundary and the other to reflect the contrast difference between the object and background. Secondly, by computing the motion vector of the contour from the difference of the two consecutive frames, we can move the snake pointers of the previous frame near the region where the object boundary is probable at the current frame. Computer experiments show that the proposed method is more robust to the complicated background than the previously known methods and can track the object with fast movement.

• Journal of Korea Multimedia Society
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• 제16권6호
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• pp.746-755
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• 2013

This paper presents a three dimensional bilateral filter detecting target trajectory, extracting spatial target information using two dimensional bilateral filter and temporal target information using one dimensional bilateral filter. In order to discriminate edge pixel with flat background and target region spatially and temporally, spatial and temporal variance are used for an image and temporal profile. With this procedure, background and background profile are predicted without original target through two dimensional and one dimensional bilateral filter. Finally, using spatially predicted background and temporally predicted background profile, small target can be detected. For comparison of existing target detection methods and the proposed method, the receiver operating characteristics (ROC) is used in experimental results. Experimental results show that the proposed method has superior target detection rate and lower false alarm rate.