• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.733-735
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• 2018

최근의 차량 주차관리 시설, 출입통제가 필요한 장소 그리고 도로 방범카메라를 통한 단속 등 다양한 곳에서 차량 번호판 자동 인식 기술들이 활용되고 있다. 하지만 현재 사용되고 있는 LPR(License Plate Recognition) 시스템에는 많은 장비와 비용이 들어간다는 큰 단점이 존재한다. 본 논문에서는 하나의 컴퓨터와 최소의 카메라를 가지고 할 수 있는 기계학습을 통한 영상처리를 제안하려 한다. 먼저 딥러닝 프레임워크 중 하나인 YOLO(You Only Look Once) [4]를 활용하여 자동차의 번호판 부분의 영역을 검출하고 Grayscale를 통해 햇빛 또는 조명 등의 영향을 감소시켜 번호판의 특징을 보존시킨다. 전처리 작업이 끝난 후 번호판에서 숫자를 인식 하는 부분에서는 k-NN(k-Nearest Neighbor) 알고리즘을 사용하였으며 한글 문자 인식부분은 Template Matching을 이용하였다. 제안한 알고리즘을 사용하여 기존 LPR 시스템에서 획득한 차량이미지를 대상으로 시뮬레이션 한 결과 좋은 결과를 얻을 수 있어 향후 연구 방향의 시스템 확장성의 가능성을 발견할 수 있었다.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.103-113
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• 2019

License plate recognition camera is dedicated device designed for acquiring images of the target vehicle for recognizing letters and numbers in a license plate. Mostly, it is used as a part of the system combined with server and image analysis module rather than as a single use. However, building a system for vehicle license plate recognition is costly because it is required to construct a facility with a server providing the management and analysis of the captured images and an image analysis module providing the extraction of numbers and characters and recognition of the vehicle's plate. In this study, we would like to develop an embedded type convergent camera (Edge Base) which can expand the function of the camera to not only the license plate recognition but also the security CCTV function together and to perform two functions within the camera. This embedded type convergence camera equipped with a high resolution 4K IP camera for clear image acquisition and fast data transmission extracted license plate area by applying YOLO, a deep learning software for multi object recognition based on open source neural network algorithm and detected number and characters of the plate and verified the detection accuracy and recognition accuracy and confirmed that this camera can perform CCTV security function and vehicle number plate recognition function successfully.

• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.4
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• pp.39-48
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• 2016

An information management system for a solid waste landfill site was developed, in this study, to optimize the operation and management of solid waste landfill in real time in addition to provide the information of landfill status to the landfill operator, public official concerned and local residents. The landfill information management system is composed of two systems (Solid waste landfill history management system and landfill operation and performance management system). The solid waste landfill history management system based on automated RFID/LPR system allows landfill operators to provide information of waste collection vehicles and received waste. In addition, the system aids in the identification of 3-dimensional (3D) position for landfilled solid wastes. Using the landfill operation and performance management system based on 3D laser scanner delivers information about landfill volume, settlement, landfill density, and current landfill capacity to landfill operators in real time, resulting in optimum space utilization. Ultimately, this system would dramatically reduce exposure of landfill operators to hazardous materials and improve the productivity of landfill operations.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2016.11a
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• pp.116.1-116.1
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• 2016

반도체 가스센서에서는 가연성 및 탄화수소계 가스를 감지 하기 위해서 $100{\sim}500^{\circ}C$ 이상의 동작온도를 필요로 한며, 이에 따라 반도체식 가스센서의 마이크로 히터 소재는 고온에서 열적 안정성이 있는 소재가 요구된다. 현재 상용화되고 있는 반도체식 가스센서는 실리콘(Silicon) 기반의 MEMS 기술을 이용한 가스센서이며, 구조적으로나 성능적 한계가 드러남에 따라 실리콘 이외의 다양한 재료의 MEMS 응용기술 개발이 필요한 실정이다. 본 연구에서는 이러한 실리콘의 재료적 한계를 극복하기 위해 다공성 알루미늄 산화물(AAO)을 기판으로 사용하여 마이크로 히터를 제작하였다. AAO의 제작에 앞서 CMP, 화학연마, 전해연마를 이용하여 적합한 전처리 공정을 선정하였고, AAO 제작 시 온도, 시간, 전압의 변수를 주어 마이크로 히터 기판에 적합한 공정을 탐색하였다. 마이크로 플랫폼은 MEMS 공정으로 제작되었으며, PR(Photo Resist)을 LPR(Liquid Photo Resist)과 DFR(Dry Film Resist)로 각각 2종 씩 선택하여 AAO에 적합한 제품을 선정하였다. 제작된 마이크로 히터는 $1.8mm{\times}1,8mm$로 소형화 하였고, 열손실의 제어를 위해 열확산 방지층을 추가하였다. 구동 온도, 소비전력, 장시간 구동시 안정성의 측정 및 평가는 적외선 열화상 카메라와 kiethly 2420 source meter를 이용하여 측정하였으며, 열확산 방지층의 유 무에 따른 온도 분포 및 소비전력을 비교평가 하였다. 최종적으로는 현재 사용화 되어있는 가스센서들의 소비전력과 비교 평가 하여 논의 하였다.

• Journal of IKEEE
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• v.18 no.4
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• pp.471-477
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• 2014

In this paper, we propose a low-cost license plate recognition system based on smart cam system using Android. The proposed system consists of a portable device and server. Potable device Hardware consists of ARM Cortex-A9 (S5PV210) processor control unit, a power supply device, wired and wireless communication, input/output unit. We develope Linux kernel and dedicated device driver for WiFi module and camera. The license plate recognition algorithm is consisted of setting candidate plates areas with canny edge detector, extracting license plate number with Labeling, recognizing with template matching, etc. The number that is recognized by the device is transmitted to the remote server via the user mobile phone, and the server re-transfer the vehicle information in the database to the portable device. To verify the utility of the proposed system, user photographs the license plate of any vehicle in the natural environment. Confirming the recognition result, the recognition rate was 95%. The proposed system was suitable for low cost portable license plate recognition device, it enabled the stability of the system when used long time by using the Android operating system.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.423-431
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• 2016

In general LPR(License Plate Recognition) in outdoor image is not so simple differently from in the image captured from manmade environment, because of geometric shape distortion and large illumination changes. this paper proposes three techniques for LPR in outdoor images captured from CCTV. At first, a serially connected multi-stage Adaboost LP detector is proposed, in which different complementary features are used. In the proposed detector the performance is increased by the Haar-like Adaboost LP detector consecutively connected to the MB-LBP based one in serial manner. In addition the technique is proposed that makes image processing easy by the prior determination of LP type, after correction of geometric distortion of LP image. The technique is more efficient than the processing the whole LP image without knowledge of LP type in that we can take the appropriate color to gray conversion, accurate location for separation of text/numeric character sub-images, and proper parameter selection for image processing. In the proposed technique we use DBN(Deep Belief Network) to achieve a robust character recognition against stroke loss and geometric distortion like slant due to the incomplete image processing.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.95-101
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• 2014

This paper explains effective tracking method for a vehicle cutting in a line on the road automatically. The method employs KLT based on optical flow using play-back image sequence. Main contribution of this paper is play-back image sequence that is in order image frames for rewind direction from a reference point in time. The moment when recognizing camera can read a license plate very well can usually be the reference point in time. The biggest images of object traced can usually be obtained at this moment also. When optic flow is applied, the bigger image of the object traced can be obtained, the more feature points can be obtained. More many feature points bring good result of tracking object. After the recognizing cameras read a license plate on the vehicle suspected of cut-in-line violation, and then the system extracts the play-back image sequence from the tracking cameras for watching wide range. This paper compares using play-back image sequence as normal method for tracking to using play-forward image sequence as suggested method on the results of the experiment and also shows the suggested algorithm has a good performance that can be applied to the unmanned system for watching cut-in-line violation.