• Journal of Advanced Marine Engineering and Technology
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• 제25권2호
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• pp.365-374
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• 2001

Its a tendency to strengthen related international was as the importance on marine oil pollution recently becomes the issue. According to the regulation of IMO, oil discharge from ships is allowed under 15PPM only and oil filtering equipment is essential. Oily water separator of laminated plate type which is one of gravity type separator can be use as assistant equipment for the oil filtering system to meet the present IMO standard, because it fits well to process large amount of rich oil with high specific gravity. The purpose of this paper is to investigate an efficiency of oil/water separation with the characteristics of laminated plate arrangement. The analyse of oil contents for oil-water mixture were carried out in order to find an efficiency of oil/water separation and an experimental study was simultaneously carried out to investigate internal flow characteristics of separator by visualization method and PIV(Particle Image Velocimetry) measurement at three spaces of plates for 5, 10 and 15 mm with variation of inlet flow rates of $0.25m^3$/h and $0.5m^3$/h. The experimental results showed that the space of the plates acts a significant role in the separating process.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 추계학술대회논문집B
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• pp.87-92
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• 2000

This study is to investigate the heat transfer characteristics the for a round turbulent jet impinging on the flat plate with and without rib. Liquid crystal/transient method was used to determine the Nusselt number distributions along the surface. The temperature on the surface was measured using liquid crystal and a digital color image processing system. The experiments were made fur the jet Reynolds number (Re) 23,000, the dimensionless nozzle-to-surface distance (L/d) from 2 to 10, and the rib type [height ($d_1$) 2mm, pitch (p) from 12 to 36mm]. It was found that for $L/d{\ge}6$ the average Nusselt numbers on the flat plate with rib type C ($p/d_1=16$) are higher than those without rib, mainly due to an increase in the turbulent intensity caused by flow separation, recirculation and reattachment on the wall surface.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3488-3500
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• 2020

At the present time, the economy continues to flourish, and private cars have become the means of choice for most people. Therefore, the license plate recognition technology has become an indispensable part of intelligent transportation, with research and application value. In recent years, the convolution neural network for image classification is an application of deep learning on image processing. This paper proposes a strategy to improve the YOLO model by studying the deep learning convolutional neural network (CNN) and related target detection methods, and combines the OpenCV and TensorFlow frameworks to achieve efficient recognition of license plate characters. The experimental results show that target detection method based on YOLO is beneficial to shorten the training process and achieve a good level of accuracy.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 추계학술대회 논문집
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• pp.872-898
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• 2007

전동차 자동검사 장치의 하나인 판타그라프 습판마모 자동측정 시스템은 첨단 기술인 머신비젼 기법을 이용하여 습판체의 마모상태를 검수자의 육안검사 없이 마모량과 교체시점 등을 판단하는 시스템이다. 본 논문에서는 우천시 빗물로 인한 노이즈(Noise)가 영상에 입력되어 판타그라프 습판의 에지(Edge)를 검출하는데 영향을 미쳐 신뢰성을 저하시키는 요인이 된다. 이러한 노이즈 제거를 위해 평활화(Smoothing) 처리로서 필터링 기법을 적용한 평균 마스크(Averaging mask), 중간값 필터(Median filter) 기법을 사용하여 문제점 등을 확인하고, 머신비젼 기술에서 사용되는 영상측정에 있어 에지 추출(Edge Detection)이 노이즈의 영향을 받지 않고 안정된 결과를 획득할 수 있도록 유도하고자 한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권3호
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• pp.166-171
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• 2009

In recent years, video detection systems have been implemented in various infrastructures such as airport, public transportation, power generation system, water dam and so on. Recognizing moving objects in video sequence is an important problem in computer vision, with applications in several fields, such as video surveillance and target tracking. Segmentation and tracking of multiple vehicles in crowded situations is made difficult by inter-object occlusion. In the system described in this paper, the mean shift algorithm is firstly used to filter and segment a color vehicle image in order to get candidate regions. These candidate regions are then analyzed and classified in order to decide whether a candidate region contains a license plate or not. And then some characters in the license plate is recognized by using the fuzzy ARTMAP neural network, which is a relatively new architecture of the neural network family and has the capability to learn incrementally unlike the conventional BP network. We finally design a license plate recognition system using the mean shift algorithm and fuzzy ARTMAP neural network and show its performance via some computer simulations.

• 대한기계학회논문집
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• 제16권8호
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• pp.1566-1574
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• 1992

본 연구에서는 원형수직 충돌분류에 의한 가열평판의 전열특성을 해석하기 위 하여 최근 표면온도 측정에 많이 사용되고 있는 liquid crystal을 이용하였다. 즉 liquid crystal의 감온특성과 영상처리 기법을 이용하여 레이놀즈수 및 노즐과 충돌판 사이의 거리(L/D) 변화에 따른 전열면의 온도장 변화를 측정하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1256-1259
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• 2002

In this paper, we have proposed license plate recognition system for multi-national vehicle license plate using geometric features along with hybrid and seven segment pattern vectors. In the proposed system, we suggested to find horizontal and vertical relation after going through preparation process with inputted real-time license plate image of Korea and Japan, and then to classify license plate with using characteristic and geometric information of license plates. It classifies the extracted license plate images into letters and numbers, such as local name, local number, classification character and license consecutive numbers, and recognize license plate of Korea and Japan by applying hybrid and seven segments pattern vectors to classified letter and number region. License plate extraction step of the proposed system uses width and length information along with relative rate of Korean and Japanese license plate. Moreover, it exactly segmentation by letters with using each letter and number position information within license plate region, and recognizes Korean and Japanese license plates by applying hybrid and seven segment pattern vectors, containing characteristics related to letter size and movement within segmented letter area. As the result of testing the proposed system in real experiment, it recognized regardless of external lighting conditions as well as classifying license plates by nations, Korea and Japan. We have developed a system, recognizing regardless of inputted structural character of vehicle licenses and external environment.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 추계학술대회 학술발표 논문집 제16권 제2호
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• pp.203-207
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• 2006

Nowadays, Cars are continuing to grow at an alarming rate but they also cause many problems such as traffic accident, pollutions and so on. One of the most effective methods that prevent traffic accidents is the use of traffic monitoring systems, which are already widely used in many countries. The monitoring system is beginning to be used in domestic recently. An intelligent monitoring system generates photo images of cars as well as identifies cars by recognizing their plates. That is, the system automatically recognizes characters of vehicle plates. An automatic vehicle plate recognition consists of two main module: a vehicle plate locating module and a vehicle plate number identification module. We study for a vehicle plate number identification module in this paper. We use image preprocessing, feature extraction, multi-layer neural networks for recognizing characters of vehicle plates and we present a feature-comparison method for improving the performance of vehicle plate number identification module. In the experiment on identifying vehicle plate number, 300 images taken from various scenes were used. Of which, 8 images have been failed to identify vehicle plate number and the overall rate of success for our vehicle plate recognition algorithm is 98%.

• 한국융합학회논문지
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• 제9권9호
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• pp.31-39
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• 2018

본 논문에서는 차량 주변 환경의 변화에서도 번호판 영역을 검출하는 연구를 하였다. 그래서 주변 환경 변화에 적응하는 윤곽선 추출 기반의 자동차 번호판 검출 방법을 제안하였다 제안하는 방법은 윤곽선 추출 과정에서 불필요한 잡음 부분을 제거하기 위해 DoG(Difference of Gaussian)을 이용하여 윤곽선을 추출 하였다. 추출한 윤곽선 영상를 이진화하여 Mophology operation을 사용하여 문자부분 윤곽선을 강조시켰다. 그리고 문자의 종횡비를 판별하여 번호판의 문자와 유사한 비율의 윤곽선을 추출하였다. 그리고 윤곽이 가장 길게 이어진 경우를 차량 번호판으로 추정하여 검출 하였다. 본 연구에서는 차량 정면 뿐 아니라 기울어져 있는 차량의 번호판, 차량 주변 환경의 변화를 가지는 차량 번호판 등 다양한 130개의 차량 영상 데이터를 사용하였다. 그리고 번호판의 패턴이 다른 오토바이 영상에서도 실험 하였다. 실험 결과 기울어져 있는 영상은 93%, 다양한 배경 환경에서는 90% 오토바이영상에서는 70%의 검출률을 나타냈으나 정면의 영상에서 98%의 검출률을 나타내었다.

• 전자공학회논문지
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• 제50권8호
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• pp.187-195
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• 2013

차량 번호판 검출의 기존 연구들은 대부분 높은 성능을 얻기 위해 영상 획득 환경을 제한한다. 본 논문은 제약사항이 적은 환경에서 다양한 종류의 차량 번호판을 검출하기 위해 SIFT와 신경망을 이용한 새로운 방법을 제안한다. SIFT는 영상의 크기, 회전 변화에 불변하는 지역특징으로서 처리해야 할 환경이 고정되지 않은 경우에도 분별력이 뛰어나다. 영상에서 추출한 SIFT를 번호판 내부의 것(내부 부류)과 외부의 것(외부 부류)으로 나누어 2부류 분류기를 학습한다. 분류기는 신경망을 사용하며, 찾고자 하는 번호판의 종류를 학습 집합에 포함하는 것으로 다양한 종류의 번호판을 동일한 알고리즘으로 검출할 수 있다. 제안하는 방법은 입력 영상에서 지역특징을 추출하고 미리 학습한 분류기로 번호판 내부 부류를 가려낸다. 분류기의 성능이 높지 않더라도 분류 결과 내부 부류는 번호판 내부에 밀집하여 나타나고 번호판 외부에서는 흩어져 나타난다. 이러한 특성을 이용해 지역특징 맵을 만들고, 이 맵에서 임계값 이상인 전역 최댓값을 번호판 영역으로 검출한다. 다양한 환경에서 데이터 베이스를 수집하고 지역특징 분류와 번호판 검출 알고리즘을 실험한다. 지역특징을 분류기로 분류한 결과 정인식률은 97.1%, 정확률은 62.0%, 재현율은 50.2%를 보였다. 정인식률에 비해 정확률과 재현율은 낮았지만, 번호판 검출 결과 98.6%의 높은 검출 성능을 보였다.