• Title/Summary/Keyword: 주변잡음제거

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A Vehicle License Plate Recognition Using the Feature Vectors based on Mesh and Thinning (메쉬 및 세선화 기반 특징 벡터를 이용한 차량 번호판 인식)

  • Park, Seung-Hyun;Cho, Seong-Won
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.705-711
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    • 2011
  • This paper proposes an effective algorithm of license plate recognition for industrial applications. By applying Canny edge detection on a vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are compared with the pre-learned weighting values by backpropagation neural network to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

A Vehicle License Plate Recognition Using the Haar-like Feature and CLNF Algorithm (Haar-like Feature 및 CLNF 알고리즘을 이용한 차량 번호판 인식)

  • Park, SeungHyun;Cho, Seongwon
    • Smart Media Journal
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    • v.5 no.1
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    • pp.15-23
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    • 2016
  • This paper proposes an effective algorithm of Korean license plate recognition. By applying Haar-like feature and Canny edge detection on a captured vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are classified using neural networks trained by backpropagation algorithm to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

Tracking ond Distance Measurement of the Moving Object in Stereo Camera System as a Security Equipment (방범 설비의 스테레오 카메라 시스템에서 이동객체의 추적과 거리측정)

  • 이재수;홍권의;손영우
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.17 no.4
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    • pp.106-115
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    • 2003
  • In crossing stereo camera system as a security equipment system, a new algorithm for the tracking method of the moving object and the measurement method of distance of the object from cameras to moving object is proposed. The stereo input images are matched by a pixel for the moving object extraction, then the moving elements obtained from an adaptive threshold's value for an error correction and the moving object area extracted by noise eliminative algorithm. In addition to, the moving object traced by control pan/tilt of cameras using a coordinate value of the moving object, and the measurement method of distance to moving object by using special features of the crossing stereo camera system is proposed. From the experimental results, the proposed algorithm was found to be able to measure of the distance and trace for moving object in a stereo security camera system. The error rate of a distance measurement be existed within 6%. Moreover in implementation the proposed algorithm, the stereo security system, the automatic moving robot system and the stereo remote control system will be applied practical application.

A Study on 2D/3D image Conversion Method using Create Depth Map (2D/3D 변환을 위한 깊이정보 생성기법에 관한 연구)

  • Han, Hyeon-Ho;Lee, Gang-Seong;Lee, Sang-Hun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.4
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    • pp.1897-1903
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    • 2011
  • This paper discusses a 2D/3D conversion of images using technologies like object extraction and depth-map creation. The general procedure for converting 2D images into a 3D image is extracting objects from 2D image, recognizing the distance of each points, generating the 3D image and correcting the image to generate with less noise. This paper proposes modified new methods creating a depth-map from 2D image and recognizing the distance of objects in it. Depth-map information which determines the distance of objects is the key data creating a 3D image from 2D images. To get more accurate depth-map data, noise filtering is applied to the optical flow. With the proposed method, better depth-map information is calculated and better 3D image is constructed.

Time Series Analysis of Agricultural Reservoir Water Level Data for Abnormal Behavior Detection (농업용 저수지 이상거동 탐지를 위한 시계열 수위자료 특성 분석)

  • Lee, Sung Hack;Lee, Sang Hyun;Hong, Min Ki;Cho, Jin Young
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.275-275
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    • 2015
  • 최근 기후변화에 따른 극한 강우사상의 증가로 인하여 농업용 저수지의 재해 위험도가 증가하고 있는 추세이며, 사고가 발생할 때 마다 파손/붕괴된 시설물을 보수하는 대응형 유지관리체계에서 벗어나 기반시설의 성능과 생애주기 등을 고려하여 재해 발생을 사전에 예보 및 경보를 알릴 수 있는 예방적 관리체계로의 전환이 필요하다. 한국농어촌공사는 전국 1,500개 저수지에서 10분 단위 수위자료를 측정하고 있으며, 이를 분석하여 재해예방에 활용할 수 있는 기반이 조성되어 있으나 이에 대한 관리가 이루어지지 않고 있고 수집된 자료를 활용하여 재해 징후를 분석할 수 있는 재해 예방적 분석기술이 마련되어 있지 않은 실정이다. 본 연구에서는 농업용 저수지 수위자료를 이용한 저수지 이상거동을 판별하기 위하여 전국 34개 한국농어촌공사 관할 저수의 시계열 수위자료의 특성(Feature)을 분석하고자 한다. 시계열 자료의 시계열 특성을 분석하기 위하여 한국농어촌공사 관할의 전국 34개 저수지를 선정하여 분석을 실시하였다. 대상저수지는 지역별, 저수용량, 안정등급, 붕괴발생, 1개 지사관할 저수지로 각각 구분하여 선정하였으며, 각 저수지의 수위 측정기간(최소 5개년)에 대한 자료를 수집하였다. 농업용 저수지의 시계열 수위 자료의 특성을 분석하기 위하여 자료의 전처리를 수행하였다. 자료의 전처리는 시계열 수위자료의 잡음 특성, 기상자료 관련 변동특성 등 분류(Classification)에 영향을 미치는 노이즈 요소를 제거하는 과정이다. 전처리과정을 거친 자료는 특징(Feature) 추출 과정을 거치게 되고, 추출된 특징의 적합성에 따라 분류 알고리듬 성능에 많은 영향을 미친다. 따라서 시계열 자료의 특성을 파악하고 특징을 추출하는 것은 이상치 탐지에 있어 매우 중요한 과정이다. 본 연구에서는 시계열 자료 특징 추출 방법으로 물리적인 한계치, 확률적인 문턱값(Threshold), 시계열 패턴, 주변 저수지와의 시계열 상관분석 등을 적용하였으며, 이를 데이터베이스로 구축하여 이후 분류알고리듬 학습에 적용하여 정상치와 이상치를 판별하는데 이용될 수 있도록 하였다. 따라서 본 연구에서 제시되는 농업용 저수지의 시계열 특성은 다양한 분류알고리듬에 적용할 수 있으며, 이를 통하여 저수지 이상거동 판별을 위한 최적을 분류알고리듬의 선택에 도움이 될 것이다.

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Interference Analysis of ATC System by Lawn Mower (예초기(Lawn mower)에 의한 항공이동통신시설 간섭 분석)

  • Lee, Doo-Hyun;Kang, Young-heung
    • Journal of Advanced Navigation Technology
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    • v.26 no.5
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    • pp.338-343
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    • 2022
  • The Air Radio Station plays a role in creating skyways for aircraft and helping them fly safely through aviation mobile communication facilities (U/VHF transceivers) and various navigation safety facilities. It is necessary to remove large trees and weeds around the aircraft because accurate and safe signals must be provided without interruption. During the mowing work for the efficient management of landscaping facilities, there have been cases in which noise is introduced by Lawn Mower, which hinders control work. Accordingly, in order to analyze how mower affects air mobile communication facilities, the interference effect on air mobile communication facilities was analyzed for four types of mower, two-stroke, and battery type. As a result of the analysis, it was found that the two-stroke mower greatly affects air mobile communication facilities.

Robust Scheme of Segmenting Characters of License Plate on Irregular Illumination Condition (불규칙 조명 환경에 강인한 번호판 문자 분리 기법)

  • Kim, Byoung-Hyun;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.11
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    • pp.61-71
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    • 2009
  • Vehicle license plate is the only way to check the registrated information of a vehicle. Many works have been devoted to the vision system of recognizing the license plate, which has been widely used to control an illegal parking. However, it is difficult to correctly segment characters on the license plate since an illumination is affected by a weather change and a neighboring obstacles. This paper proposes a robust method of segmenting the character of the license plate on irregular illumination condition. The proposed method enhance the contrast of license plate images using the Chi-Square probability density function. For segmenting characters on the license plate, binary images with the high quality are gained by applying the adaptive threshold. Preprocessing and labeling algorithm are used to eliminate noises existing during the whole segmentation process. Finally, profiling method is applied to segment characters on license plate from binary images.

Evaluation of 2D Shear Wave Velocity Imaging of Subground Using HWAW Method (HWAW 기법을 이용한 지반의 2차원 전단파 속도 평가)

  • Kim, Jong-Tae;Park, Hyung-Choon;Bang, Eun-Seok;Park, Heon-Joon;Kim, Dong-Soo
    • Journal of the Korean Society for Nondestructive Testing
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    • v.27 no.2
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    • pp.105-114
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    • 2007
  • Two-dimensional imaging of $V_s$ profile becomes more important in Korea because of the large horizontal variation of soil stiffness. To obtain a shear-wave velocity profile in geotechnical practice, various seismic nondestructive investigation methods are being frequently used. In this study, harmonic wavelet analysis of wave (HWAW) method is applied to the determination of $V_s$ profile to overcome some of weaknesses in the existing surface wave methods. HWAW method which is based on time-frequency analysis using harmonic wavelet transform has been developed to determine phase and group velocities of waves. Field testing of this method is relatively simple and fast because one experimental setup which consists of one pair of receivers is needed to determine $V_s$ profile of site. The proposed method uses the signal portion of the maximum local signal/noise ratio to evaluate the phase velocity to minimize the effects of noise, and uses single array inversion which considers receiver locations. Field tests were performed in 2 sites in order to evaluate accuracy of test method and estimate the applicability of 2-D imaging by HWAW method. Through field applications and comparison with other test results, the good accuracy and applicability of the proposed method were verified.

Pace and Facial Element Extraction in CCD-Camera Images by using Snake Algorithm (스네이크 알고리즘에 의한 CCD 카메라 영상에서의 얼굴 및 얼굴 요소 추출)

  • 판데홍;김영원;김정연;전병환
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2002.11a
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    • pp.535-542
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    • 2002
  • 최근 IT 산업이 급성장하면서 화상 회의, 게임, 채팅 등에서의 아바타(avatar) 제어를 위한 자연스러운 인터페이스 기술이 요구되고 있다. 본 논문에서는 동적 윤곽선 모델(active contour models; snakes)을 이용하여 복잡한 배경이 있는 컬러 CCD 카메라 영상에서 얼굴과 눈, 입, 눈썹, 코 등의 얼굴 요소에 대해 윤곽선을 추출하거나 위치를 파악하는 방법을 제안한다. 일반적으로 스네이크 알고리즘은 잡음에 민감하고 초기 모델을 어떻게 설정하는가에 따라 추출 성능이 크게 좌우되기 때문에 주로 단순한 배경의 영상에서 정면 얼굴의 추출에 사용되어왔다 본 연구에서는 이러한 단점을 파악하기 위해, 먼저 YIQ 색상 모델의 I 성분을 이용한 색상 정보와 차 영상 정보를 사용하여 얼굴의 최소 포함 사각형(minimum enclosing rectangle; MER)을 찾고, 이 얼굴 영역 내에서 기하학적인 위치 정보와 에지 정보를 이용하여 눈, 입, 눈썹, 코의 MER을 설정한다. 그런 다음, 각 요소의 MER 내에서 1차 미분과 2차 미분에 근거한 내부 에너지와 에지에 기반한 영상 에너지를 이용한 스네이크 알고리즘을 적용한다. 이때, 에지 영상에서 얼굴 주변의 복잡한 잡음을 제거하기 위하여 색상 정보 영상과 차 영상에 각각 모폴로지(morphology)의 팽창(dilation) 연산을 적용하고 이들의 AND 결합 영상에 팽창 연산을 다시 적용한 이진 영상을 필터로 사용한다. 총 7명으로부터 양 눈이 보이는 정면 유사 방향의 영상을 20장씩 취득하여 총 140장에 대해 실험한 결과, MER의 오차율은 얼굴, 눈, 입에 대해 각각 6.2%, 11.2%, 9.4%로 나타났다. 또한, 스네이크의 초기 제어점을 얼굴은 44개, 눈은 16개, 입은 24개로 지정하여 MER추출에 성공한 영상에 대해 스네이크 알고리즘을 수행한 결과, 추출된 영역의 오차율은 각각 2.2%, 2.6%, 2.5%로 나타났다.해서 Template-based reasoning 예를 보인다 본 방법론은 검색노력을 줄이고, 검색에 있어 Feasibility와 Admissibility를 보장한다.매김할 수 있는 중요한 계기가 될 것이다.재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of

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A Novel Method for Automated Honeycomb Segmentation in HRCT Using Pathology-specific Morphological Analysis (병리특이적 형태분석 기법을 이용한 HRCT 영상에서의 새로운 봉와양폐 자동 분할 방법)

  • Kim, Young Jae;Kim, Tae Yun;Lee, Seung Hyun;Kim, Kwang Gi;Kim, Jong Hyo
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.2
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    • pp.109-114
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    • 2012
  • Honeycombs are dense structures that small cysts, which generally have about 2~10 mm in diameter, are surrounded by the wall of fibrosis. When honeycomb is found in the patients, the incidence of acute exacerbation is generally very high. Thus, the observation and quantitative measurement of honeycomb are considered as a significant marker for clinical diagnosis. In this point of view, we propose an automatic segmentation method using morphological image processing and assessment of the degree of clustering techniques. Firstly, image noises were removed by the Gaussian filtering and then a morphological dilation method was applied to segment lung regions. Secondly, honeycomb cyst candidates were detected through the 8-neighborhood pixel exploration, and then non-cyst regions were removed using the region growing method and wall pattern testing. Lastly, final honeycomb regions were segmented through the extraction of dense regions which are consisted of two or more cysts using cluster analysis. The proposed method applied to 80 High resolution computed tomography (HRCT) images and achieved a sensitivity of 89.4% and PPV (Positive Predictive Value) of 72.2%.