• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.338-341
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• 2013

눈동자 검출은 운전 부주의 검출, 졸음 검출, 시선 검출 등 다양한 상황 인지에 이용되고 있다. 이러한 상황 인지를 위해 본 논문에서는 원 허프 변환(Hough Circle Transform)을 이용한 눈동자 검출방법을 제안한다. 이것은 영상 내 원을 검출하는 방법으로 연산량이 많아 실시간 처리에 문제가 된다. 이러한 문제를 해결하기 위해 눈 검출 후 눈 영역의 크기를 일정한 눈 크기로 정규화 하고 눈의 양쪽 끝점간 거리에 따른 대략적인 눈동자의 반지름 값 범위를 추정한다. 그 추정된 반지름 값 범위 내에서 Hough Circle Transform을 수행하면 연산량의 축소가 가능하며 그 결과 초당 21frames 정도의 눈동자 검출이 가능하였다.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1057-1062
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• 2014

This paper proposes a tip-over detection method for a mobile robot using a support inscribed circle defined as an inscribed circle of a support polygon. A support polygon defined by the contact points between the robot and the terrain is often used to analyze the tip-over. For a robot moving on uneven terrain, if the intersection between the extended line of gravity from the robot's COG and the terrain is inside the support polygon, tip-over will not occur. On the contrary, if the intersection is outside, tip-over will occur. The terrain is detected by using an RGB-D sensor. The terrain is locally modeled as a plane, and thus the normal vector can be obtained at each point on the terrain. The support polygon and the terrain's normal vector are used to detect tip-over. However, tip-over cannot be detected in advance since the support polygon is determined depending on the orientation of the robot. Thus, the support polygon is approximated as its inscribed circle to detect the tip-over regardless of the robot's orientation. To verify the effectiveness of the proposed method, the experiments are carried out using a 4-wheeled robot, ERP-42, with the Xtion RGB-D sensor.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.782-794
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• 2013

This paper proposes the wafer position recognition algorithm using camera. First, for eliminating the image distortions caused by the illumination and the irregular camera position, the wafer image is restored as a circle through projective transformation. Next, we use edge detection algorithm to extract the wafer's edge and then apply Generalized Symmetry Transform(GST) to extract a circle. The GST evaluates symmetry between two points by combining a distance weight function, a phase weight function, and a logarithmic mapping of the points' intensities and detecting interest regions. Trough several experiments, we found out the proposed method is able to prevent the cleaning system and the wafer from damaging.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.410-413
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• 2009

Wafer pre-alignment is to find the center and the orientation of a wafer and to move the wafer to the desired position and orientation. In this paper, an area camera based pre-aligning method is presented that captures 8 wafer images regularly during 360 degrees rotation. From the images, wafer edge positions are extracted and used to estimate the wafer's center and orientation using least square circle fitting. These information are utilized for the proper alignment of the wafer.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.7
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• pp.578-589
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• 1991

In this paper, there is proposed a novel concept of Incremintal Circle Transform which can describe the boundary contour of a two-dimensional object without object without occlusions. And a pattern recognition algorithm to determine the posture of an object is developed with the aid of line integral and similarity transform. Also, It is confirmed via experiments that the algorithm can find the posture of an object in a very fast manner independent of the starting point for boundary coding and the position of the object.

• ETRI Journal
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• v.32 no.6
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• pp.871-880
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• 2010

Many applications dealing with image management need a technique for removing duplicate images or for grouping related (near-duplicate) images in a database. This paper proposes a concentric circle-based image signature which makes it possible to detect near-duplicates rapidly and accurately. An image is partitioned by radius and angle levels from the center of the image. Feature values are calculated using the average or variation between the partitioned sub-regions. The feature values distributed in sequence are formed into an image signature by hash generation. The hashing facilitates storage space reduction and fast matching. The performance was evaluated through discriminability and robustness tests. Using these tests, the particularity among the different images and the invariability among the modified images are verified, respectively. In addition, we also measured the discriminability and robustness by the distribution analysis of the hashed bits. The proposed method is robust to various modifications, as shown by its average detection rate of 98.99%. The experimental results showed that the proposed method is suitable for near-duplicate detection in large databases.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.822-831
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• 2003

A computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and the radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation is introduced for line detection. The dimension of inner and outer radius of pipe is calculated by the proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified and removed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.946-950
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• 2003

In this paper, a computer-vision based pipe shape inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle. by which pipes with wrong end-shape can be classified removed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.521-525
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• 2002

In this paper, a computer-vision based pipe-inspection algorithm is developed. The algorithm uses the modified Hough transformation and a line-scanning approach to identify the edge line and radius of the pipe image, from which the eccentricity and dimension of the pipe-end is calculated. Line and circle detection was performed using Laplace operator with input image, which are acquired from the front and side cameras. In order to minimize the memory usage and the processing time, a clustering method with the modified Hough transformation for line detection. The dimension of inner and outer radius of pipe is calculated by proposed line-scanning method. The method scans several lines along the X and Y axes, calculating the eccentricity of inner and outer circle, by which pipes with wrong end-shape can be classified removed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.97-100
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• 2006

최근 절전에 대한 의식이 높아짐에 따라 이 문제를 해결하기 위해 많은 연구가 진행되고 있다. 본 논문은 건물 내의 인체를 검지하여 불필요한 전력 소모를 줄이기 위한 방법으로써 카메라를 통하여 실시간으로 영상을 취득하여 인체의 유무를 판단하기 위한 알고리즘을 구현하였다. 실험을 통하여 제안된 방법이 환경 변화에 강인한 특성과 인체 검출율이 우수함을 보이고자 한다.