• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2381-2383
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• 2003

This paper presents an effective approach to dynamic obstacle avoidance for mobile robot. The main concept of this approach includes modified polar mapping for recognition of the moving obstacle in vision-based robot systems. To simplify the segmentation of the moving obstacle from the background and to obtain its relative position data the modified polar mapping is proposed. Dynamic moving obstacles are avoided with a vision sensor and stationary obstacles are avoided with a sonar sensor.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.34.1-34
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• 2002

1. Introduction 2. Focus of Expansion 3. Log-Polar Mapping 4. Egomotion and Optical Flow 5. Experimental Results 6. Conclusion. References.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.295-298
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• 2006

본 논문에서는 극 좌표계에서의 벡터 표현 방식을 이용한 per-pixel displacement mapping 방법을 제시한다. per-pixel displacement mapping은 triangle mesh의 처리 방식에 상관없이 변위매핑을 수행할 수 있도록 한 것으로, 2차원 screen space로 projection 된 triangle의 각 pixel의 위치를 객체 표면 정보에 따라 displacement 해주는 방법이다. 이는 기 검증된 범프매칭 하드웨어에 약간의 하드웨어를 추가함으로써 변위매핑을 수행할 수 있도록 한 효과적인 구조이다. 제안 방식에 의해 생성된 영상과 기존 방식에 의해 생성된 영상을 비교해본 결과, 시각적으로 거의 차이가 없음을 알 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.379-385
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• 2004

Medical images are being managed more by PACS in general medical institutions. It is important to protect patients from being invaded their privacy related to the images. It is also necessary to confirm the ownership, the right of property of the medical images and notice whether the data are modified. In this paper, we propose a robust watermarking against RST attacks in medical images on the PACS. The proposed scheme modifies and improves Log-Polar Mapping and Fourier Mellin Transform in order to realize and recover serious image degradation and watermark data loss caused by the conversion between cartesian coordinate and log-polar coordinate. We used the radius and theta Look Up Table to solve the realization of the Fourier Mellin Transform, and inserted a watermark into 2D-DFT magnitudes using Spread Spectrum. Experimental results shows that this method are robust to rotation attack.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.455-461
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• 2002

This paper presents a new parametric log line equation of polar form for Hough transform in log-polar plane, in which it can remove the well-known unboundedness problem of Hough parameters. Bolduc's method is used to generate a log-polar image dividing the fovea and periphery from a Cartesian image. Edges of the fovea and periphery are detected by using the Sobel mask and the proposed space-variant gradient mask, and are combined in the log-polar plane. The sampled points that might constitute a log line are quite sparse in a deep peripheral region due to severe under-sampling, which is an inherent property of LPM. To cope with such under-sampling, we determine the values of cumulative cells in Hough space by using the space-variant weighting. In our experiments, the proposed method demonstrates its validity of detecting not only the lines passing through both the fovea and periphery but also the lines in a deep periphery.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.3 s.94
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• pp.335-343
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• 2005

In this paper, we propose a method to classify inverse synthetic aperture radar(ISAR) image from different target. The approach can provide efficient features for classification by the combined use of a polar mapping procedure and a well-designed classifier The resulting feature vectors are able to meet requirements that efficient features should have : invariance with respect to rotation and scale, small dimensionality, as well as highly discriminative information. Typical experimental examples of the proposed method are provided and discussed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.11
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• pp.1063-1069
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• 2011

NCTR(Non-Cooperative Target Recognition) and ATR(Automatic Target Recognition) are methodologies to identify military targets using radar, optical, and infrared images. Among them, a strategy to recognize ground targets using synthetic aperature radar(SAR) images is called SAR ATR. In general, SAR ATR consists of three sequential stages: detection, discrimination and classification. In this paper, a modification of the polar mapping classifier(PMC) to identify inverse SAR(ISAR) images has been made in order to apply it to SAR ATR. In addition, a preprocessing scheme can mitigate the effect from the clutter, and information on the shadow is employed to improve the classification accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.896-899
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• 1996

A new algorithm for planning a collision free path is developed based on linear parametric curve. A collision-free path is viewed as a connected space curve in which the path consists of two straight curve connecting start to target point. A single intermediate connection point is considered in this paper and is used to manipulate the shape of path by organizing the control point in polar coordinate (.theta.,.rho.). The algorithm checks interference with obstacles, defined as GM (Geometry Mapping), and maps obstacles in Euclidean Space into images in CPS (Connection Point Space). The GM for all obstacles produces overlapping images of obstacle in CPS. The clear area of CPS that is not occupied by obstacle images represents collision-free paths in Euclidean Space. Any points from the clear area of CPS is a candidate for a collision-free path. A simulation of GM for number of cases are carried out and results are presented including mapped images of GM and performances of algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1312-1317
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• 2003

This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.241-246
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• 2004

Medical images are being managed more by PACS in general medical institutions. It is important to protect patients from being invaded their privacy related to the images. It is also necessary to confirm the ownership, the right of properity of the medical images and notice whether the data are modified. In this paper, we propose a robust watermarking against RST attacks in medical images on the PACS. The proposed scheme modifies and improves Log-Polar Mapping and Fourier Mellin Transform in order to realize and recover serious image degradation and watermark data loss caused by the conversion between cartesian coordinate and log-polar coordinate. We used the radius and theta Look Up Table to solve the realization of the Fourier Mellin Transform, and inserted a watermark into 2D-DFT magnitudes using Spread Spectrum. Experimental results shows that this method are robust to several attack.