• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.4 no.2
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• pp.38-45
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• 1995

The diagnosis and monitoring system of abnormal cutting condition is necessary to realize precision machining proces and factory automation, which are final goal of metal cutting in order to develop this system, theimage processing technique has been investigated in machining process. In theis paper, the measurement system of tool wear using computer vision is designed to detect the wear pattern by non-contact and direct method and get the realiable wear information about cutting tool. We measured the area of the side and front part of the diamond core dril which is used in 40kHz ultrasonic vibration machine.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.2
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• pp.81-87
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• 2013

Motion segmentation is a fundamental technique for analysing image sequences of real scenes. A process of identifying moving objects from data is a typical task in many computer vision applications. In this paper, we propose motion segmentation that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modeling. Motion segmentation in this paper covers RGB video data.

• Journal of Broadcast Engineering
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• v.10 no.2
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• pp.156-165
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• 2005

This paper presents a new auto brighoess control algorithm fur adaptive background subtraction. The algorithm is designed to cope with the problem of auto-brightness adjustment feature of consumer-type cameras. The experimental results show the proposed method improves performance of the classification. This will be beneficial to many computer vision applications in term of reducing the cost of implementation and making them more available to the mass consumer market.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.52-54
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• 2021

In this paper we propose a method predict whether a video frame contains motion according to the invoking situation of the coding unit mode in HEVC. The motion prediction of video frames is conducive for use in video compression and video data extraction. In the existing technology, motion prediction is usually performed by high complexity computer vision technology. However, we proposed to analyze the motion frame based on HEVC coding unit mode which does not need to use the static background frame. And the prediction accuracy rate of motion frame analysis by our method has exceeded 80%.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.621-626
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• 2015

This paper presents a camera calibration method in order to estimate the lane detection and inter-vehicle distance estimation system for an automotive safety driving system. In order to implement the lane detection and vision-based inter-vehicle distance estimation to the embedded navigations or black box systems, it is necessary to consider the computation time and algorithm complexity. The process of camera calibration estimates the horizon, the position of the car's hood and the lane width for extraction of region of interest (ROI) from input image sequences. The precision of the calibration method is very important to the lane detection and inter-vehicle distance estimation. The proposed calibration method consists of three main steps: 1) horizon area determination; 2) estimation of the car's hood area; and 3) estimation of initial lane width. Various experimental results show the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3935-3949
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• 2017

In this paper, a novel multiple description image coding (MDC) scheme is proposed, which is based on the characteristics of the human visual model. Due to the inherent characteristics of human vision, the human eye can only perceive the change of the specific thresholds, that is, the just noticeable difference (JND) thresholds. Therefore, JND model is applied to improve MDC syetem. This paper calculates the DCT coefficients firstly, and then they are compared with the JND thresholds. The data that is less than the JND thresholds can be neglected, which will improve the coding efficiency. Compared with other existing methods, the experimental results of the proposed method are superior.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1039-1042
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• 2011

스트레스는 다양한 질병의 원인이 되며 스트레스의 해소는 질병 예방에 중요한 요인이라 할 수 있을 것이다. 스트레스를 해소시키는 방법 중 한 가지는 청각이나 시각을 이용하는 방법이다. 청각과 시각을 동시에 이용할 수 있다면 그 효과를 극대화 할 수 있을 것이다. 본 논문에서는 음악의 분위기를 자동으로 파악하고, 파악한 음악의 분위기를 표현할 수 있는 감성조명 시스템을 제안하였다. 본 논문에서 제시한 감성조명을 공원이나 가정집 등에 제공할 수 있을 것이고, 음악과 조명을 동시에 제공함으로 현대인 질병의 원인이라 할 수 있는 스트레스 해소가 가능 할 것이다. 또한 본 논문의 시스템을 이용하여 임상실험을 실시하여 임상데이터를 확보한다면 심리 치료를 목적으로 하는 의학적 도구로 발전 할 수 있을 것으로 보인다.

• Smart Media Journal
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• v.8 no.2
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• pp.66-73
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• 2019

Recently, object recognition technology using computer vision has attracted attention as a technology to replace sensor-based object recognition technology. It is often difficult to commercialize sensor-based object recognition technology because such approach requires an expensive sensor. On the other hand, object recognition technology using computer vision may replace sensors with inexpensive cameras. Moreover, Real-time recognition is viable due to the growth of CNN, which is actively introduced into other fields such as IoT and autonomous vehicles. Because object recognition model applications demand expert knowledge on deep learning to select and learn the model, such method, however, is challenging for non-experts to use it. Therefore, in this paper, we analyze the structure of deep - learning - based object recognition models, and propose a platform that can automatically select a deep - running object recognition model based on a user 's desired condition. We also present the reason we need to select statistics-based object recognition model through conducted experiments on different models.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2138-2144
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• 2016

People with visual disabilities suffer environmentally, socially, and technologically. Navigating through places and recognizing objects are already a big challenge for them who require assistance. This study aimed to develop an android-based assistive application for the visually impaired. Specifically, the study aimed to create a system that could aid visually impaired individuals performs significant tasks through object recognition and identifying locations through GPS and Google Maps. In this study, the researchers used an android phone allowing a visually impaired individual to go from one place to another with the aid of the application. Google Maps is integrated to utilize GPS in identifying locations and giving distance directions and the system has a cloud server used for storing pinned locations. Furthermore, Haar-like features were used in object recognition.

• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.97-102
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• 2017

Object detection and tracking have become one of the most active research areas in the past few years, and play an important role in computer vision applications over our daily life. Many tracking techniques are proposed, and Camshift is an effective algorithm for real time dynamic object tracking, which uses only color features, so that the algorithm is sensitive to illumination and some other environmental elements. This paper presents and implements an effective moving object detection and tracking to reduce the influence of illumination interference, which improve the performance of tracking under similar color background. The implemented prototype system recognizes object using invariant features, and reduces the dimension of feature descriptor to rectify the problems. The experimental result shows that that the system is superior to the existing methods in processing time, and maintains better problem ratios in various environments.