• 제목/요약/키워드: Image Features

검색결과 3,382건 처리시간 0.031초

INTERACTIVE FEATURE EXTRACTION FOR IMAGE REGISTRATION

  • Kim Jun-chul;Lee Young-ran;Shin Sung-woong;Kim Kyung-ok
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.641-644
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    • 2005
  • This paper introduces an Interactive Feature Extraction (!FE) approach for the registration of satellite imagery by matching extracted point and line features. !FE method contains both point extraction by cross-correlation matching of singular points and line extraction by Hough transform. The purpose of this study is to minimize user's intervention in feature extraction and easily apply the extracted features for image registration. Experiments with these imagery dataset proved the feasibility and the efficiency of the suggested method.

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SWT -based Wavelet Filter Application for De-noising of Remotely Sensed Imageries

  • Yoo Hee-Young;Lee Kiwon;Kwon Byung-Doo
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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    • pp.505-508
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    • 2005
  • Wavelet scheme can be applied to the various remote sensing problems: conventional multi-resolution image analysis, compression of large image sets, fusion of heterogeneous sensor image and segmentation of features. In this study, we attempted wavelet-based filtering and its analysis. Traditionally, statistical methods and adaptive filter are used to manipulate noises in the image processing procedure. While we tried to filter random noise from optical image and radar image using Discrete Wavelet Transform (DW1) and Stationary Wavelet Transform (SW1) and compared with existing methods such as median filter and adaptive filter. In result, SWT preserved boundaries and reduced noises most effectively. If appropriate thresholds are used, wavelet filtering will be applied to detect road boundaries, buildings, cars and other complex features from high-resolution imagery in an urban environment as well as noise filtering

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An Effective Relevance Feedbackbased Image Retrieval using Color and Texture

  • Jung, Sung-Hwan
    • 한국멀티미디어학회논문지
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    • 제6권4호
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    • pp.746-752
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    • 2003
  • In this paper, we proposed an image retrieval system with a simple and effective relevance feedback, called RAP(Reward and Punishment) algorithm. First, color and texture features were extracted from the images. Next, the extracted feature values were used for image retrieval in various forms. We applied the relevance feedback to the initial retrieved images from the image retrieval system, and compared its result with that of the conventional system. In the experiment using the test image database of 16 class 512 images, the proposed system showed the better retrieval performance of about 10∼l7 % than that of the conventional INRIA system in each relevance feedback step.

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A Novel Image Completion Algorithm Based on Planar Features

  • Xiao, Mang;Liu, Yunxiang;Xie, Li;Chen, Qiaochuan;Li, Guangyao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권8호
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    • pp.3842-3855
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    • 2018
  • A novel image completion method is proposed that uses the advantage of planar structural information to fill corrupted portions of an image. First, in estimating parameters of the projection plane, the image is divided into several planes, and their planar structural information is analyzed. Second, in calculating the a priori probability of patch and patch offset regularity, this information is converted into a constraint condition to guide the process of filling the hole. Experimental results show that the proposed algorithm is fast and effective, and ensures the structure continuity of the damaged region and smoothness of the texture.

SIFT 와 SURF 알고리즘의 성능적 비교 분석 (Comparative Analysis of the Performance of SIFT and SURF)

  • 이용환;박제호;김영섭
    • 반도체디스플레이기술학회지
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    • 제12권3호
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    • pp.59-64
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    • 2013
  • Accurate and robust image registration is important task in many applications such as image retrieval and computer vision. To perform the image registration, essential required steps are needed in the process: feature detection, extraction, matching, and reconstruction of image. In the process of these function, feature extraction not only plays a key role, but also have a big effect on its performance. There are two representative algorithms for extracting image features, which are scale invariant feature transform (SIFT) and speeded up robust feature (SURF). In this paper, we present and evaluate two methods, focusing on comparative analysis of the performance. Experiments for accurate and robust feature detection are shown on various environments such like scale changes, rotation and affine transformation. Experimental trials revealed that SURF algorithm exhibited a significant result in both extracting feature points and matching time, compared to SIFT method.

영상 특징 선택을 위한 유전 알고리즘 (Genetic Algorithm for Image Feature Selection)

  • 신영근;박상성;장동식
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2006년도 한국컴퓨터종합학술대회 논문집 Vol.33 No.1 (B)
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    • pp.193-195
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    • 2006
  • As multimedia information increases sharply, In image retrieval field the method that can analyze image data quickly and exactly is required. In the case of image data, because each data includes a lot of informations, between accuracy and speed of retrieval become trade-off. To solve these problem, feature vector extracting process that use Genetic Algorithm for implementing prompt and correct image clustering system in case of retrieval of mass image data is proposed. After extracting color and texture features, the representative feature vector among these features is extracted by using Genetic Algorithm.

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The Application of Dyadic Wavelet In the RS Image Edge Detection

  • Qiming, Qin;Wenjun, Wang;Sijin, Chen
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1268-1271
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    • 2003
  • In the edge detection of RS image, the useful detail losing and the spurious edge often appear. To solve the problem, we use the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, we obtain the RS image of a certain appropriate scale, and figure out the edge data of the plane and the upright directions respectively, then work out the grads vector module of the surface features, at last by tracing them we get the edge data of the object therefore build the RS image which obtains the checked edge. This method can depress the effect of noise and examine exactly the edge data of the object by rule and line. With an experiment of a RS image which obtains an airport, we certificate the feasibility of the application of dyadic wavelet in the object edge detection.

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Evaluation of Volumetric Texture Features for Computerized Cell Nuclei Grading

  • Kim, Tae-Yun;Choi, Hyun-Ju;Choi, Heung-Kook
    • 한국멀티미디어학회논문지
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    • 제11권12호
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    • pp.1635-1648
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    • 2008
  • The extraction of important features in cancer cell image analysis is a key process in grading renal cell carcinoma. In this study, we applied three-dimensional (3D) texture feature extraction methods to cell nuclei images and evaluated the validity of them for computerized cell nuclei grading. Individual images of 2,423 cell nuclei were extracted from 80 renal cell carcinomas (RCCs) using confocal laser scanning microscopy (CLSM). First, we applied the 3D texture mapping method to render the volume of entire tissue sections. Then, we determined the chromatin texture quantitatively by calculating 3D gray-level co-occurrence matrices (3D GLCM) and 3D run length matrices (3D GLRLM). Finally, to demonstrate the suitability of 3D texture features for grading, we performed a discriminant analysis. In addition, we conducted a principal component analysis to obtain optimized texture features. Automatic grading of cell nuclei using 3D texture features had an accuracy of 78.30%. Combining 3D textural and 3D morphological features improved the accuracy to 82.19%. As a comparative study, we also performed a stepwise feature selection. Using the 4 optimized features, we could obtain more improved accuracy of 84.32%. Three dimensional texture features have potential for use as fundamental elements in developing a new nuclear grading system with accurate diagnosis and predicting prognosis.

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판타지 영화에 표현된 여성 캐릭터 의상의 조형적 특성 (Expressive Effects of Female Characters' Costumes Expressed in Fantasy Movies)

  • 김수경;이인성
    • 복식문화연구
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    • 제16권5호
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    • pp.963-978
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    • 2008
  • This study examined the images and formative features of female characters portrayed in fantasy films. This study aimed at providing an applicable theory to modern fashion by reconsidering the images of women appearing in fantasy films and arranging fantastical features reflected in costumes of female characters. The followings were the results of the study: The first divine nature that human beings discovered was woman nature. The discovered stone worked of the prehistoric age had a meaning of the great mother of universe and expressed a positive image. Such positive images of the goddess were variously differentiated to negative images or reduced in their roles and meanings in the settlement process of patriarchy as well as sociocultural transition. The foremost examples of negative image were expressed as grotesque, destructive, otherness, sensual, and exotic. The positive image of a goddess in fantasy films was not especially emphasized. On the other hand, the negative images of the goddess and the case of costumes were variously expressed as well as emphasized the typicality of the negative image of the characters. It was reconsidered that the typical features of characters in fantasy films were a result of the image of women following sociocultural transition. In addition, it was confirmed that such result was being reflected in film costume.

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특징점 기반 확률 맵을 이용한 단일 카메라의 위치 추정방법 (Localization of a Monocular Camera using a Feature-based Probabilistic Map)

  • 김형진;이동화;오택준;명현
    • 제어로봇시스템학회논문지
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    • 제21권4호
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    • pp.367-371
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    • 2015
  • In this paper, a novel localization method for a monocular camera is proposed by using a feature-based probabilistic map. The localization of a camera is generally estimated from 3D-to-2D correspondences between a 3D map and an image plane through the PnP algorithm. In the computer vision communities, an accurate 3D map is generated by optimization using a large number of image dataset for camera pose estimation. In robotics communities, a camera pose is estimated by probabilistic approaches with lack of feature. Thus, it needs an extra system because the camera system cannot estimate a full state of the robot pose. Therefore, we propose an accurate localization method for a monocular camera using a probabilistic approach in the case of an insufficient image dataset without any extra system. In our system, features from a probabilistic map are projected into an image plane using linear approximation. By minimizing Mahalanobis distance between the projected features from the probabilistic map and extracted features from a query image, the accurate pose of the monocular camera is estimated from an initial pose obtained by the PnP algorithm. The proposed algorithm is demonstrated through simulations in a 3D space.