• 제목/요약/키워드: Feature-based image matching

검색결과 339건 처리시간 0.032초

Improved image alignment algorithm based on projective invariant for aerial video stabilization

  • Yi, Meng;Guo, Bao-Long;Yan, Chun-Man
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권9호
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    • pp.3177-3195
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    • 2014
  • In many moving object detection problems of an aerial video, accurate and robust stabilization is of critical importance. In this paper, a novel accurate image alignment algorithm for aerial electronic image stabilization (EIS) is described. The feature points are first selected using optimal derivative filters based Harris detector, which can improve differentiation accuracy and obtain the precise coordinates of feature points. Then we choose the Delaunay Triangulation edges to find the matching pairs between feature points in overlapping images. The most "useful" matching points that belong to the background are used to find the global transformation parameters using the projective invariant. Finally, intentional motion of the camera is accumulated for correction by Sage-Husa adaptive filtering. Experiment results illustrate that the proposed algorithm is applied to the aerial captured video sequences with various dynamic scenes for performance demonstrations.

웨이브렛 변환을 이용한 내용기반 검색 시스템 (Content-based retrieval system using wavelet transform)

  • 반가운;유기형;박정호;최재호;곽훈성
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 하계종합학술대회논문집
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    • pp.733-736
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    • 1998
  • In this paper, we propose a new method for content-based retrieval system using wavelet transform and correlation, which has were used in signal processing and image compressing. The matching method is used not perfect matching but similar matching. Used feature vector is the lowest frequency(LL) itself, energy value, and edge information of 4-layer, after computng a 4-layer 2-D fast wavelet transform on image. By the proosed algorithm, we got the result that was faste rand more accurate than the traditional algorithm. Because used feature vector was compressed 256:1 over original image, retrieval speed was highly improved. By using correlation, moving object with size variation was reterieved without additional feature information.

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Finger Vein Recognition based on Matching Score-Level Fusion of Gabor Features

  • Lu, Yu;Yoon, Sook;Park, Dong Sun
    • 한국통신학회논문지
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    • 제38A권2호
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    • pp.174-182
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    • 2013
  • Most methods for fusion-based finger vein recognition were to fuse different features or matching scores from more than one trait to improve performance. To overcome the shortcomings of "the curse of dimensionality" and additional running time in feature extraction, in this paper, we propose a finger vein recognition technology based on matching score-level fusion of a single trait. To enhance the quality of finger vein image, the contrast-limited adaptive histogram equalization (CLAHE) method is utilized and it improves the local contrast of normalized image after ROI detection. Gabor features are then extracted from eight channels based on a bank of Gabor filters. Instead of using the features for the recognition directly, we analyze the contributions of Gabor feature from each channel and apply a weighted matching score-level fusion rule to get the final matching score, which will be used for the last recognition. Experimental results demonstrate the CLAHE method is effective to enhance the finger vein image quality and the proposed matching score-level fusion shows better recognition performance.

HAQ 알고리즘과 Moment 기반 특징을 이용한 내용 기반 영상 검색 알고리즘 (Content-Based Image Retrieval Algorithm Using HAQ Algorithm and Moment-Based Feature)

  • 김대일;강대성
    • 대한전자공학회논문지SP
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    • 제41권4호
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    • pp.113-120
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    • 2004
  • 본 논문은 내용 기반 검색 기법에 의한 보다 효율적인 특징 추출 및 영상 검색 알고리즘을 제안하였다. 먼저, MPEG 비디오의 key frame을 입력 영상으로 하여 Gaussian edge detector를 이용하여 객체를 추출하고, 그에 따른 객체 특징들, location feature distributed dimension feature와 invariant moments feature를 추출하였다. 다음, 제안하는 HAQ (Histogram Analysis and Quantization) 알고리즘으로 characteristic color feature를 추출하였다. 마지막으로 key frame이 아닌 shot frame을 질의영상으로 하여 제안된 matching 기법에 따라 4가지 특징들의 단계별 검색을 수행하였다. 본 논문의 목적은 사용자가 요구하는 장면이 속한 비디오의 shot 경계 내의 key frame을 검색하는 새로운 내용 기반 검색 알고리즘을 제안함에 있다. 제안된 알고리즘을 바탕으로 10개의 뮤직비디오, 836개의 시험 영상으로 실험한 결과, 효과적인 검색 효율을 보였다.

Content Based Image Retrieval Based on A Novel Image Block Technique Combining Color and Edge Features

  • Kwon, Goo-Rak;Haoming, Zou;Park, Sei-Seung
    • Journal of information and communication convergence engineering
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    • 제8권2호
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    • pp.185-190
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    • 2010
  • In this paper we propose the CBIR algorithm which is based on a novel image block method that combined both color and edge feature. The main drawback of global histogram representation is dependent of the color without spatial or shape information, a new image block method that divided the image to 8 related blocks which contained more information of the image is utilized to extract image feature. Based on these 8 blocks, histogram equalization and edge detection techniques are also used for image retrieval. The experimental results show that the proposed image block method has better ability of characterizing the image contents than traditional block method and can perform the retrieval system efficiently.

저니키 모멘트 기반 지역 서술자를 이용한 실시간 특징점 정합 (Real-Time Feature Point Matching Using Local Descriptor Derived by Zernike Moments)

  • 황선규;김회율
    • 대한전자공학회논문지SP
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    • 제46권4호
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    • pp.116-123
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    • 2009
  • 서로 다른 시점의 두 영상에서 동일한 점들을 정합하는 특징점 정합은 다양한 영상 처리 분야에서 널리 사용되고 있으며, 최근에는 실시간으로 동작하는 특징점 정합에 대한 요구가 높아지고 있다. 본 논문은 저니키 모멘트 기반의 지역 서술자를 이용하여 특징점을 실시간으로 정합하는 방법을 제안한다. 빠른 모서리 점 검출 방법을 이용하여 입력 영상으로부터 특징점을 추출하고, 각 특징점에서 저니키 모멘트를 이용한 지역 서술자를 생성한다. 저니키 모멘트 기반의 지역 서술자는 특징점 주변의 부분 영상을 적은 차수의 특징 벡터로써 효율적으로 표현하며, 영상의 회전과 밝기 변화에 강인하다. 본 논문에서는 저니키 모멘트 계산을 실시간으로 수행하기 위하여 고정된 크기의 저니키 기저 함수를 미리 계산하여 이를 룩업 테이블에 저장하여 사용한다. 특징점 정합 단계에서는 근사 최근방 이웃(ANN) 방법을 사용하여 초기 정합 결과를 얻고, 이 중 잘못된 정합은 RANSAC 알고리즘을 이용하여 제거함으로써 최종 정합 결과를 얻는다. 실험 결과 제안하는 방법은 다양한 변환이 존재하는 영상에 대하여 실시 간으로 특징점 정합을 수행함을 확인하였다.

새로운 하이브리드 스테레오 정합기법에 의한 3차원 선소추출 (3D Line Segment Detection using a New Hybrid Stereo Matching Technique)

  • 이동훈;우동민;정영기
    • 대한전기학회논문지:시스템및제어부문D
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    • 제53권4호
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    • pp.277-285
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    • 2004
  • We present a new hybrid stereo matching technique in terms of the co-operation of area-based stereo and feature-based stereo. The core of our technique is that feature matching is carried out by the reference of the disparity evaluated by area-based stereo. Since the reference of the disparity can significantly reduce the number of feature matching combinations, feature matching error can be drastically minimized. One requirement of the disparity to be referenced is that it should be reliable to be used in feature matching. To measure the reliability of the disparity, in this paper, we employ the self-consistency of the disunity Our suggested technique is applied to the detection of 3D line segments by 2D line matching using our hybrid stereo matching, which can be efficiently utilized in the generation of the rooftop model from urban imagery. We carry out the experiments on our hybrid stereo matching scheme. We generate synthetic images by photo-realistic simulation on Avenches data set of Ascona aerial images. Experimental results indicate that the extracted 3D line segments have an average error of 0.5m and verify our proposed scheme. In order to apply our method to the generation of 3D model in urban imagery, we carry out Preliminary experiments for rooftop generation. Since occlusions are occurred around the outlines of buildings, we experimentally suggested multi-image hybrid stereo system, based on the fusion of 3D line segments. In terms of the simple domain-specific 3D grouping scheme, we notice that an accurate 3D rooftop model can be generated. In this context, we expect that an extended 3D grouping scheme using our hybrid technique can be efficiently applied to the construction of 3D models with more general types of building rooftops.

Refinement of Disparity Map using the Rule-based Fusion of Area and Feature-based Matching Results

  • Um, Gi-Mun;Ahn, Chung-Hyun;Kim, Kyung-Ok;Lee, Kwae-Hi
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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    • pp.304-309
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    • 1999
  • In this paper, we presents a new disparity map refinement algorithm using statistical characteristics of disparity map and edge information. The proposed algorithm generate a refined disparity map using disparity maps which are obtained from area and feature-based Stereo Matching by selecting a disparity value of edge point based on the statistics of both disparity maps. Experimental results on aerial stereo image show the better results than conventional fusion algorithms in the disparity error. This algorithm can be applied to the reconstruction of building image from the high resolution remote sensing data.

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2D 지역푸리에변환 기반 텍스쳐 특징 서술자에 관한 연구 (Texture Feature Extractor Based on 2D Local Fourier Transform)

  • 뮤잠멜;팽소호;김현수;김덕환
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2009년도 춘계학술발표대회
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    • pp.106-109
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    • 2009
  • Recently, image matching becomes important in Computer Aided Diagnosis (CAD) due to the huge amount of medical images. Specially, texture feature is useful in medical image matching. However, texture features such as co-occurrence matrices can't describe well the spatial distribution of gray levels of the neighborhood pixels. In this paper we propose a frequency domain-based texture feature extractor that describes the local spatial distribution for medical image retrieval. This method is based on 2D Local Discrete Fourier transform of local images. The features are extracted from local Fourier histograms that generated by four Fourier images. Experimental results using 40 classes Brodatz textures and 1 class of Emphysema CT images show that the average accuracy of retrieval is about 93%.

Feature matching toy Omnidirectional Image based on Singular Value Decomposition

  • Kim, Do-Yoon;Lee, Young-Jin;Myung jin Chung
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2002년도 ICCAS
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    • pp.98.2-98
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    • 2002
  • $\textbullet$ Omnidirectional feature matching $\textbullet$ SVD-based matching algorithm $\textbullet$ Using SSD instead of the zero-mean correlation $\textbullet$ The similarity with the Gaussian weighted $\textbullet$ Low computational cost $\textbullet$ It describes the similarity of the matched pairs in omnidirectional images.

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