• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.532-534
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• 2011

최근 입체 콘텐츠 및 디스플레이의 지속적인 발전과 관심도가 증가하고 있고, 입체 변환에 대한 연구가 활발히 진행되어지고 있다. 본 논문에서는 단일 카메라로부터 획득한 다수의 영상을 이용하여 최적의 입체영상을 선택하는 방법에 대하여 제안한다. 이러한 방식은, 스테레오 카메라를 이용하여 입체를 제작하는 방식과 단일 영상의 깊이 정보를 이용하여 입체로 변환하는 방식의 단점을 없애고 장점을 가져올 수 있다. N 장의 영상을 획득한 후, 에지의 방향성을 계산하여 주각을 구한다. 또한 임의의 두 장을 선택한 후 두 영상에 대한 프로젝션 데이터를 구하여 상관관계를 계산한 후, 이를 이용하여 이동벡터를 구한다. 이 두 가지 변수를 이용하여 최적의 입체영상을 선택하고, 입체로 시청 가능하도록 보정한 후 입체영상으로 제작한다. 실험에서는 분석을 수행하여 성능을 평가한다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.03b
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• pp.5-5
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• 2010

The depth of the object pointed by the laser beam is computed depending on the pixel position on the CCD There involved several number of internal and external parameters such as inter-pixel distance, focal length, position and orientation of the system components in the depth measurement error. In this paper, it is shown through the error sensitivity analysis of the parameters that the most important parameters in the sense of error sources are the angle of the laser beam and the inter pixel distance. Also, the calibration technique to minimize their effect for the depth computation is proposed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.501-506
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• 2000

Many research in Robot control has effectively proceeded on the development of Aritficial Intelligence Robot which is able to apply to the uncertain and monotonous operations which are repeated continuously in the industrial field. In this study, the precise shape recognition of base metal for welding was gained by mono CCD camera, and the gained data was transformed into Decimal code through Image Board in computer. And the Fuzzy Logic control system designed by use of Fuzzy rule was built to judge whether the base metals were precisely matched or not with Decimal code. Machanically manipulated Robot syst em was linked to Fuzzy Control system through image information, and ultimately, these systems will be able to apply for production system.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.485-488
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• 2002

In this paper, fuzzy logic controllers are designed for compensation of distance errors. Because we can't know information of the depth in a mono camera, these errors are occurred. Also, they are increased as a target object is to keep away from a center of image. Therefore, the errors for each position of joints of an arm robot should be modeled, but accurate models can't be obtained because of no information of the depth, uncertain feature points of image, parameter uncertainties, and illumination. Hence, fuzzy logic controllers for each error are designed for compensation. This paper consists of color image processing, error modeling, and the controller design. Experimental results are given to verify the effectiveness of our proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.346-352
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• 2011

This paper presents a system of road extraction for traffic images from a single camera. The road in the images is subject to large changes in appearance because of environmental effects. The proposed system is based on the integration of color correlograms and random forest. The color correlogram depicts the color properties of an image properly. Using the random forest, road extraction is formulated as a learning paradigm. The combined effects of color correlograms and random forest create a robust system capable of extracting the road in very changeable situations.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.293-300
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• 2019

In this paper, an Embedded solution for fast navigation and precise positioning of mobile robots by floor features is introduced. Most of navigation systems tend to require high-performance computing unit and high quality sensor data. They can produce high accuracy navigation systems but have limited application due to their high cost. The introduced navigation system is designed to be a low cost solution for a wide range of applications such as toys, mobile service robots and education. The key design idea of the system is a simple localization approach using line features of the floor and delayed localization strategy using topological map. It differs from typical navigation approaches which usually use Simultaneous Localization and Mapping (SLAM) technique with high latency localization. This navigation system is implemented on single board Raspberry Pi B+ computer which has 1.4 GHz processor and Redone mobile robot which has maximum speed of 1.1 m/s.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.130-134
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• 2020

This paper proposes a new method for the digit recognition on a 7-segment display. The proposed method uses morphological processing that dilates segments of digits and connects them into strokes. The digits are extracted by connected component analysis and finally, template matching method recognizes the extracted digits. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. Experiments were conducted by using various 7-segment LED displays and 7-segment mono LCD displays. The results show that the proposed method is successful for the digit recognition on the 7-segment displays.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.65-71
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• 2014

This paper present the multi-modal user distance estimation system using mono camera and mono microphone basically equipped with a mobile device. In case of a distance estimation method using an image, we is estimated a distance of the user through the skin color region extraction step, a noise removal step, the face and eyes region detection step. On the other hand, in case of a distance estimation method using speech, we calculates the absolute difference between the value of the sample of speech input. The largest peak value of the calculated difference value is selected and samples before and after the peak are specified as the ROI(Region of Interest). The samples specified perform FFT(Fast Fourier Transform) and calculate the magnitude of the frequency domain. Magnitude obtained is compared with the distance model to calculate the likelihood. We is estimated user distance by adding with weights in the sorted value. The result of an experiment using the multi-modal method shows more improved measurement value than that of single modality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.471-479
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• 2018

Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.142-149
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• 2015

Most of the mono-camera based lane detection systems are fragile on poor illumination conditions. In order to compensate limitations of single sensor utilization, lane information fusion system using multiple lane sensors is an alternative to stabilize performance and guarantee high precision. However, conventional fusion schemes, which only concerns object detection, are inappropriate to apply to the lane information fusion. Even few studies considering lane information fusion have dealt with limited aids on back-up sensor or omitted cases of asynchronous multi-rate and coverage. In this paper, we propose a lane information fusion scheme utilizing multiple lane sensors with different coverage and cycle. The precise lane information fusion is achieved by the proposed fusion framework which considers individual ranging capability and processing time of diverse types of lane sensors. In addition, a novel lane estimation model is proposed to synchronize multi-rate sensors precisely by up-sampling spare lane information signals. Through quantitative vehicle-level experiments with around view monitoring system and frontal camera system, we demonstrate the robustness of the proposed lane fusion scheme.