• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.409-411
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• 2001

임의의 입력 영상을 이해함에 있어서 코너점은 디지털 영상의 중요한 정보가 집중되어 있기 때문에 형태를 분석하는데 있어 중요한 요소이다. 본 논문은 영상의 중요한 정보 요소인 코너점을 보다 정확하게 추출하기 위하여 Farzin Mokhtarian과 Riku Suomela가 제안한 CSS(Curvature Scale Space) 방법에 기초한 다면체 모델 방법을 이용한 새로운 알고리즘을 제안하고자 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.405-408
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• 2011

In this paper, we propose a robot remote control system based on mouth tracking. The main idea behind the work is to help disabled people who cannot operate a joystick or keyboard to control a robot with their hands. The mouth detection method in this paper is mainly based on the Adaboost feature detection approach. By using the proposed new Haar-like features for detecting the corner of mouth, the speed and accuracy of detection are improved. Combined with the Kalman filter, a continuous and accurate mouth tracking has been achieved. Meanwhile, the gripping commands of the robot manipulator were also achieved by the recognition of the user.s mouth shape, such as 'pout mouth' or 'grin mouth'. To assess the validity of the method, a mouth detection experiment and a robot cargo transport experiment were applied. The result indicated that the system can realize a quick and accurate mouse tracking; and the operation of the robot worked successfully in moving and bringing back items.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.3
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• pp.457-463
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• 2011

As computer related technologies are developed, interests in augmented reality technologies are greatly increasing. Augmented reality is a technology that composes digital contents from the real input images through camera and it enables interaction with users. This study designed a directional marker using LED light that emits infrared ray, then, provided a detection algorithm and a marker information extraction method that can realize various virtual objects as augmented reality from one marker. The newly designed method provides a solution to settle the problems in existing marker technologies such as decrease of immersiveness and read rate and single information expression, and at the same time it can minimize the cost or time consumption in marker information storage.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1499-1502
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• 2002

A method for acquiring an environmental map by integrating distance data obtained by sonars of a moving robot with web interface is proposed. Sonar data contains outliers in some cases such as ultrasonic beam is projected onto a corner of an object. Therefore, the influence of the outliers should be reduced by detecting outliers. In our method, the outliers are detected by two ways: (i) a method considering geometrical .elation among the observed surface and the projected ultrasonic beau, and (ii) a method considering consistency with data obtained by other sonars. By measurement by the sonar, the distance from the sonar to the obstacle is obtained. Assuming the two dimensional space we can know that the inside of the sector, whose renter coincide with the sonar and whose radius is equal to the obtained distance, is the free area, and a part of the arc of this sector is the obstacle area. The generation of the environmental map is done by integrating the free area and the obstacle area obtained by each measurement by the sonars. Before the integration, the outliers detection is done by two ways mentioned above. Experimental results show that obtained maps obtained by our methods with outliers defection are much better than those by a method without outliers detection.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.646-654
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• 2007

In recent years, the use of text inserted into TV contents has grown to provide viewers with better visual understanding. In this paper, video text is defined as superimposed text region located of the bottom of video. Video text extraction is the first step for video information retrieval and video indexing. Most of video text detection and extraction methods in the previous work are based on text color, contrast between text and background, edge, character filter, and so on. However, the video text extraction has big problems due to low resolution of video and complex background. To solve these problems, we propose a method to extract text from videos using the Harris corner detector. The proposed algorithm consists of four steps: corer map generation using the Harris corner detector, extraction of text candidates considering density of comers, text region determination using labeling, and post-processing. The proposed algorithm is language independent and can be applied to texts with various colors. Text region update between frames is also exploited to reduce the processing time. Experiments are performed on diverse videos to confirm the efficiency of the proposed method.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1506-1508
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• 2015

A 2D barcode region localization system for the automatic inspection of a long distance logistics objects has been developed. For the successful 2D barcode localization, variance and frequency of the pixel distribution within average 2D barcodes is modeled and the average model of 2D barcode is combined with the corner features detection to localize the final 2D barcode candidates. An automatic 2D barcode localization software was developed with the multiple features mixture method and we tested our system on real camera images of several popular 2D barcode symbologies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.69-72
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• 2011

In this paper, we propose a method to track the movement of camera from the video sequences. This method is useful for video analysis and can be applied as pre-processing step in some application such as video stabilizer and marker-less augmented reality. First, we extract the features in each frame using corner point detection. The features in current frame are then compared with the features in the adjacent frames to calculate the optical flow which represents the relative movement of the camera. The optical flow is then analyzed to obtain camera movement parameter. The final step is camera movement estimation and correction to increase the accuracy. The method performance is verified by generating a 3D map of camera movement and embedding 3D object to the video. The demonstrated examples in this paper show that this method has a high accuracy and rarely produce any jitter.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.217-223
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• 2004

In block-based lossy video compression, severe quantization causes discontinuities along block boundaries so that annoying blocking artifacts are visible in decoded video images. These blocking artifacts significantly decrease the subjective image quality. In order to reduce the blocking artifacts in decoded images, many algorithms have been proposed. However studies on so called comer outlier, have been very limited. Corner outliers make image edges look disconnected from those of neighboring blocks at cross block boundary. In order to solve this problem we propose a corner outlier detection and compensation algorithm as loop-filtering in spatial domain. Experiment results show that the proposed method provides much improved subjective image quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3086-3103
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• 2017

Video images captured by vehicle cameras often contain blurry or dithering frames due to inadvertent motion from bumps in the road or by insufficient illumination during the morning or evening, which greatly reduces the perception of objects expression and recognition from the records. Therefore, a real-time electronic stabilization method to correct fuzzy video from driving recorders has been proposed. In the first stage of feature detection, a coarse-to-fine inspection policy and a scale nonlinear diffusion filter are proposed to provide more accurate keypoints. Second, a new antiblurry binary descriptor and a feature point selection strategy for unintentional estimation are proposed, which brought more discriminative power. In addition, a new evaluation criterion for affine region detectors is presented based on the percentage interval of repeatability. The experiments show that the proposed method exhibits improvement in detecting blurry corner points. Moreover, it improves the performance of the algorithm and guarantees high processing speed at the same time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7302-7308
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• 2014

Detecting target objects robustly in natural environments is a difficult problem in the computer vision and image processing areas. This paper suggests a method of robustly detecting target objects in the environments where reflection exists. The suggested algorithm first captures scenes with a stereo camera and extracts the line and corner features representing the target objects. This method then eliminates the reflected features among the extracted ones using a homographic transform. Subsequently, the method robustly detects the target objects by clustering only real features. The experimental results showed that the suggested algorithm effectively detects the target objects in reflection environments rather than existing algorithms.