• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.334-341
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• 1998

This paper proposes an algorithm to obtain the time-to-contact between an observer and a target and surface orientation of the target. These two physical elements are computed from the image deformation of a known shape, which is extracted by supervised classification of detected line segments based on MAP and Mahalanobis distance. The proposed algorithm was applied to the natural outdoor traffic scene and would contribute to the development for a collision avoidance system.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.2
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• pp.131-139
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• 2008

This paper presents a new saliency map which is constructed by providing dynamic weights on individual features in an input image to search ROI(Region Of Interest) or FOA(Focus Of Attention). To construct a saliency map on there is no a priori information, three feature-maps are constructed first which emphasize orientation, color, and intensity of individual pixels, respectively. From feature-maps, conspicuity maps are generated by using the It's algorithm and their information quantities are measured in terms of entropy. Final saliency map is constructed by summing the conspicuity maps weighted with their individual entropies. The prominency of the proposed algorithm has been proved by showing that the ROIs detected by the proposed algorithm in ten different images are similar with those selected by one-hundred person's naked eyes.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.808-810
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• 2004

본 논문에서는 Contrast map과 Salient point를 이용하여 영상에서 중요한 객체를 자동으로 추출하는 방법을 제안한다. 우선 인간의 시각 체계와 유사한 밝기(luminance), 색상(color) 그리고 방향성(orientation) 3가지의 특징정보를 이용하여 각각의 특징정보로부터 feature map을 생성하고 이 3가지의 feature map을 선형 결합하여 contrast map을 생성한다. 이렇게 생성된 하나의 contrast map을 이용하여 대략적인 Attention Window (AW)의 위치를 결정한다. 다음으로, 영상으로부터 웨이블릿 변환을 적용하여 salient point를 찾고, salient point의 분포와 contrast map의 중요도에 따라 AW의 크기를 실제 중요 객체의 크기와 가장 유사하도록 축소시킨다. 이렇게 선택되고 축소된 AW안에서 실제 중요 객체를 추출하기 위해 AW 내부에 존재하는 영상에 대해서만 영상 분할을 하고 불필요한 영역을 제거하여 자동으로 중요객체를 추출하도록 한다.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.483-488
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• 2008

An active omni-directional raging system using an omni-directional vision with structured light has many advantages compared to the conventional ranging systems: robustness against external illumination noise because of the laser structured light and computational efficiency because of one shot image containing $360^{\circ}$ environment information from the omni-directional vision. The omni-directional range data represents a local distance map at a certain position in the workspace. In this paper, we propose a matching algorithm for the local distance map with the given global map database, thereby to localize a mobile robot in the global workspace. Since the global map database consists of line segments representing edges of environment object in general, the matching algorithm is based on relative position and orientation of line segments in the local map and the global map. The effectiveness of the proposed omni-directional ranging system and the matching are verified through experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.5
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• pp.1135-1140
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• 2007

This paper proposes an edge-based text region detection algorithm using the adaptive character-edge maps which are independent of the size of characters and the orientation of character string in natural images. First, labeled images are obtained from edge images and in order to search for characters, adaptive character-edge maps by way grammar are applied to labeled images. Next, selected label images are clustered as for distance of its neighbors. And then, text region candidates are obtained. Finally, text region candidates are verified by using the empirical rules and horizontal/vertical projection profiles based on the orientation of text region. As the results of experiments, a text region detection algorithm turned out to be robust in the matter of various character size, orientation, and the complexity of the background.

• Spatial Information Research
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• v.13 no.1 s.32
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• pp.31-41
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• 2005

In order to carry out aerial photogrammetry using GPS/INS, it is necessary to apply exterior orientation parameters, obtained while making a photo, to the editing process. It should be noted that the verification process of aerial mapping result is the most crucial process at the GPS/INS based digital photogrammetry. To this end, this study has compared the mapping result by the ways of AT results, plotter, and orientation, which is from basis of the Analytical raw map produced by the existing AT results. When comparing the horizontal and vertical accuracy of the analytical mapping with that of digital restitution, it could be found that the latter is more accurate than that of the former. In addition, it was reveled that the horizontal error was bigger than that of vertical one. Even though the accuracy of the GPS/INS based AT Direct orientation was three times poorer than the of indirect one, it was recognized that the photogrammetry process was effectively performed in the application of scale 1:5000 mapping with satisfying the allowance errors.

• Journal of the Korean Mathematical Society
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• v.32 no.4
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• pp.803-814
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• 1995

Let $\Sigma$ be the class of all complex-valued, harmonic, orientation-preserving, univalent mappings defined on $\Delta = {z : $\mid$z$\mid$ > 1}$ that map $\infty$ to $\infty$.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.987-990
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• 2005

An important issue in the field of face recognitions and man-machine interfaces is an automatic detection of faces in visual scenes. it should be computationally fast enough to allow an online detection. In this paper we describe our ongoing work on face detection that models the face appearance by edge orientation and color distribution. We show that edge orientation is a powerful feature to describe objects like faces. We present a method for face region detection using edge orientation and a method for face feature detection using local color information. We demonstrate the capability of our detection method on an image database of 1877 images taken from more than 700 people. The variations in head size, lighting and background are considerable, and all images are taken using low-end cameras. Experimental results show that the proposed scheme achieves 94% detection rate with a resonable amount of computation time.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.169-176
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• 2009

Low-cost sensors have been widely used for mobile robot navigation in recent years. However, navigation performance based on low-cost sensors is not good enough to be practically used. Among many navigation techniques, building of an accurate map is a fundamental task for service robots, and mapping with low-cost IR sensors was investigated in this research. The robot's orientation uncertainty was considered for mapping by modifying the Bayesian update formula. Then, the data association scheme was investigated to improve the quality of a built map when the robot's pose uncertainty was large. Six low-cost IR sensors mounted on the robot could not give rich data enough to align the range data by the scan matching method, so a new sample-based method was proposed for data association. The real experiments indicated that the mapping method proposed in this research was able to generate a useful map for navigation.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.429-432
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• 2001

지문영상의 특이점(Singularities) 중의 하나인 Core Point는 대부분의 지문인증 시스템에서 기준점(Reference Point)으로 사용되고 있다. 또한 Core Point의 검출은 전체 지문인증 시스템의 가장 기본적인 단계로서 전체 시스템의 성능에 많은 영향을 준다. 본 논문에서는 지문 영상의 방향 패턴(Orientation Pattern)과 이의 리레이블링(Re-labeling)을 이용한 Core Point 검출 방법을 제안하고, 기존의 Poincare Index를 이용하는 방법 및 Sine Map을 이응한 방법과 비교, 분석하였다.