• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.193-198
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• 2022

Recently, place that you need to check wearing mask and body temperature to prevent the proliferation of COVID-19 increased. But these things often measured by man manually or by machine one by one, result may be different by measuring ways, so it wastes workforce. Also, the machine generally just measures the highest temperature of the face, criteria for fever can't be trusted too. A bottleneck may occur due to crowding of people at the entrance, and because most of the measurement sites are at one entrance, it is inconvenient to track the movement of COVID-19 Confirmed cases. Thus, in this study, we intend to propose a method for suppressing the spread of infection by automatically classifying and displaying in real time using camera, thermal camera, Haar Cascade, and result selection algorithm.

• Proceedings of the KIPE Conference
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• 2012.11a
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• pp.171-172
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• 2012

본 논문에서는 Cascade buck-boost 컨버터 토폴로지에서 인덕터 전류 리플 손실을 감소시켜 효율 향상시키는 최적 스위칭 방법을 제시한다. 효율을 높이기 위한 최적 스위칭 방법은 다양한 방식으로 듀티크기와 위상을 변화시켜 인덕터 전류 리플로 인해 발생하는 손실을 비교하여 최소화하는 방식을 채택한다. 또한, 제시된 방법은 100W급 Test bed를 통해 타당성을 검증한다.

• Proceedings of the KIPE Conference
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• 2012.11a
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• pp.175-176
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• 2012

본 논문에서는 동기정류 및 부트스트랩 회로를 이용한 Cascade Buck-Boost 컨버터의 전압 제어 및 동작 모드 변경 기법을 제안한다. 제안한 방법은 기존의 제어 방법에 비해 모든 전압 영역에서 안정적으로 승 강압 모드 변경이 가능하며 높은 효율을 갖는다. 이의 검증을 위해 우선 다양한 제어 기법을 소개하고, 각각을 전압 제어 특성 및 효율 측면에서 실험적으로 비교한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6018-6033
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• 2018

Fires are a common cause of catastrophic personal injuries and devastating property damage. Every year, many fires occur and threaten human lives and property around the world. Providing early important sign for early fire detection, and therefore the detection of smoke is always the first step in fire-alarm systems. In this paper we propose an automatic smoke detection system built on camera surveillance and image processing technologies. The key features used in our algorithm are to detect and track smoke as moving objects and distinguish smoke from non-smoke objects using a convolutional neural network (CNN) model for cascade classification. The results of our experiment, in comparison with those of some earlier studies, show that the proposed algorithm is very effective not only in detecting smoke, but also in reducing false positives.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.7 no.3
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• pp.117-128
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• 1997

When computer systems with mandatory access control mechanism are interconnected each other for enforcing the MHS(Message Handling System) security on the multilevel secure distributed network environment, illegal information flow may occurs due to the unexpected cascade vulnerability problem. In this paper, new MHS security policy and security property functions are proposed for preventing the cascade vulnerability.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.7-14
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• 2019

In this paper, we propose a Cascade Classifier face detection method using the Haar-like feature, which is complemented by the Flood Fill algorithm for lossy areas due to illumination and shadow in YCbCr color space extraction. The Cascade Classifier using Haar-like features can generate noise and loss regions due to lighting, shadow, etc. because skin color extraction using existing YCbCr color space in image only uses threshold value. In order to solve this problem, noise is removed by erosion and expansion calculation, and the loss region is estimated by using the Flood Fill algorithm to estimate the loss region. A threshold value of the YCbCr color space was further allowed for the estimated area. For the remaining loss area, the color was filled in as the average value of the additional allowed areas among the areas estimated above. We extracted faces using Haar-like Cascade Classifier. The accuracy of the proposed method is improved by about 4% and the detection rate of the proposed method is improved by about 2% than that of the Haar-like Cascade Classifier by using only the YCbCr color space.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.208-214
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• 2014

Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.909-919
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• 2014

License plate (LP) detection is the most imperative part of an automatic LP recognition (LPR) system. Typical LPR contains two steps, namely LP detection (LPD) and character recognition. In this paper, we propose an efficient Vehicle-to-LP detection framework which combines with an adaptive GMM (Gaussian Mixture Model) and a cascade of boosted classifiers to make a faster vehicle LP detector. To develop a background model by using a GMM is possible in the circumstance of a fixed camera and extracts the motions using background subtraction. Firstly, an adaptive GMM is used to find the region of interest (ROI) on which motion detectors are running to detect the vehicle area as blobs ROIs. Secondly, a cascade of boosted classifiers is executed on the blobs ROIs to detect a LP. The experimental results on our test video with the resolution of $720{\times}576$ show that the LPD rate of the proposed system is 99.14% and the average computational time is approximately 42ms.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.1 s.307
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• pp.39-44
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• 2006

Pattern noise in the Delta-Sigma modulator is a well Known phenomenon that intrigued many circuit designers. These noise appear as the modulator output falls into a cyclic mode of operation. This paper addresses the dependence of these tone signal upon the system topologies. Among the four well known single-stage DSM topologies, namely Cascade of Integrators with Feedback Form(CIFB), Cascade of Integrators with Feedforward Form(CIFF), Cascade of Resonators with Feedback Form(CRFB), and Cascade of Resonators with Feedforward Form(CRFF), resonator type DSMs turn out to be more susceptible to the pattern noise than the integrator type. Noise transfer functions of the investigated topologies are also presented.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.51-57
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• 2017

Digital signage is becoming part of daily life across a wide range of visual advertisements segments market used in stations, hotels, retail stores, hotels, etc. The current digital signage system used in market is generally works on limited user interactivity with static contents. In this paper, a new approach is proposed using computer vision based dynamic audience adaptive cost-effective digital signage system. The proposed design uses the Camera attached Raspberry Pi Open source platform to employ the real-time audience interaction using computer vision algorithms to extract facial features of the audience. The real-time facial features are extracted using Haar Cascade algorithm which are used for audience gender specific rendering of dynamic digital signage content. The audience facial characterization using Haar Cascade is evaluated on the FERET database with 95% accuracy for gender classification. The proposed system, developed and evaluated with male and female audiences in real-life environments camera embedded raspberry pi with good level of accuracy.