• Title/Summary/Keyword: Shape Retrieval

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Interest Point Detection Using Hough Transform and Invariant Patch Feature for Image Retrieval

  • Nishat, Ahmad;An, Young-Eun;Park, Jong-An
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.1
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    • pp.127-135
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    • 2009
  • This paper presents a new technique for corner shape based object retrieval from a database. The proposed feature matrix consists of values obtained through a neighborhood operation of detected corners. This results in a significant small size feature matrix compared to the algorithms using color features and thus is computationally very efficient. The corners have been extracted by finding the intersections of the detected lines found using Hough transform. As the affine transformations preserve the co-linearity of points on a line and their intersection properties, the resulting corner features for image retrieval are robust to affine transformations. Furthermore, the corner features are invariant to noise. It is considered that the proposed algorithm will produce good results in combination with other algorithms in a way of incremental verification for similarity.

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Modified Borda Count Method for Combining Multiple Features of Image Retrieval (영상검색에서의 다중 피쳐 결합을 위한 변형된 보다 카운트 방법)

  • 정세윤;김규헌;전병태;이재연;배영래
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.593-596
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    • 1999
  • In this paper, we propose an image retrieval system using the MBCM(Modified Borda Count method) in CME(Combining Multiple Experts). It combines color-, shape- and texture-based retrieval sub-systems. CME method can complementarily combine results of each retrieval system, which uses different features. There are some problems when the Borda count method in pattern recognition is applied to image retrieval. Thus, we propose a modified Borda count method to solve these problems. In the experiment, our method reduces false positive errors and produces better results than that of each retrieval module that uses only one feature.

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3D partial object retrieval using cumulative histogram (누적 히스토그램을 이용한 3차원 물체의 부재 검색)

  • Eun, Sung-Jong;Hyoen, Dae-Hwan;Lee, Ki-Jung;WhangBo, Taeg-Keun
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.669-672
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    • 2009
  • The techniques extract shape descriptors from 3D models and use these descriptors for indices for comparing shape similarities. Most similarity search techniques focus on comparisons of each individual 3D model from databases. However, our similarity search technique can compare not only each individual 3D model, but also partial shape similarities. The partial shape matching technique extends the user's query request by finding similar parts of 3D models and finding 3D models which contain similar parts. We have implemented an experimental partial shape-matching search system for 3D pagoda models, and preliminary experiments show that the system successfully retrieves similar 3D model parts efficiently.

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Feature Extraction of Shape of Image Objects in Content-based Image Retrieval (내용기반으로한 이미지 검색에서 이미지 객체들의 외형특징추출)

  • Cho, June-Suh
    • The KIPS Transactions:PartB
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    • v.10B no.7
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    • pp.823-828
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    • 2003
  • The main objective of this paper is to provide a methodology of feature extraction using shape of image objects for content-based image retrieval. The shape of most real-life objects is irregular, and hence there is no universal approach to quantify the shape of an arbitrary object. In particular. electronic catalogs contain many image objects for their products. In this paper, we perform feature extraction based on individual objects in images rather than on the whole image itself, since our method uses a shape-based approach of objects using RLC lines within an image. Experiments show that shape parameters distinctly represented image objects and provided better classification and discrimination among image objects in an image database compared to Texture.

Image Retrieval using Fast Wavelet Histogram and Color Information (고속 웨이블렛 히스토그램과 색상정보를 이용한 영상검색)

  • 김주현;이배호
    • Proceedings of the IEEK Conference
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    • 2000.06d
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    • pp.194-197
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    • 2000
  • Wavelet transform used for content-based image retrieval has good performance in texture image. Image features for content-based image retrieval are color, texture, and shape. In this paper, we use color feature extracted from HSI color space known as most similar vision system to human vision system and texture feature extracted from wavelet histogram which has multiresolution property. Proposed method is compared with HSI color histogram method and wavelet histogram method. It is shown better performance.

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A Semantic-based Video Retrieval System using Method of Automatic Annotation Update and Multi-Partition Color Histogram (자동 주석 갱신 및 멀티 분할 색상 히스토그램 기법을 이용한 의미기반 비디오 검색 시스템)

  • 이광형;전문석
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.8C
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    • pp.1133-1141
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    • 2004
  • In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 90 percents.

A Content-Based Image Retrieval Technique Using the Shape and Color Features of Objects (객체의 모양과 색상특징을 이용한 내용기반 영상검색 기법)

  • 박종현;박순영;오일환
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.10B
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    • pp.1902-1911
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    • 1999
  • In this paper we present a content-based image retrieval algorithm using the visual feature vectors which describe the spatial characteristics of objects. The proposed technique uses the Gaussian mixture model(GMM) to represent multi-colored objects and the expectation maximization(EM) algorithm is employed to estimate the maximum likelihood(ML) parameters of the model. After image segmentation is performed based on GMM, the shape and color features are extracted from each object using Fourier descriptors and color histograms, respectively. Image retrieval consists of two steps: first, the shape-based query is carried out to find the candidate images whose objects have the similar shapes with the query image and second, the color-based query is followed. The experimental results show that the proposed algorithm is effective in image retrieving by using the spatial and visual features of segmented objects.

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Image Retrieval Considering Shape Information of Projection Vector (투영 벡터의 형상 정보를 이용한 영상검색)

  • Kwon, Dong-Hyun;Yi, Tai-Hong
    • Journal of KIISE:Information Networking
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    • v.28 no.4
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    • pp.651-656
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    • 2001
  • Histogram intersection method, that counts the occurrence of color pixels, is one of the easy and simple color image retrieval methods. The method has an appropriate global property but does not contain the knowledge of shape for images. The absence of spatial information makes it difficult to discriminate images of the similar histogram. The application of one-dimensional projection to each image enables to obtain shape or spatial information of image. But in this case there is another problem having different length of the projection vector according to the size of each image. Thus this paper proposes a method that uses relative distances between peaks and their maximum value in the projection vector. In order to verify retrieval performance, the experimental results between the histogram intersection method, the projection only method, and the proposed one are compared and analyzed.

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A Robust Content-Based Image Retrieval Technique for Distorted Query Image (변형된 질의 영상에 강한 내용 기반 영상 검색 기법)

  • 김익재;이제호;권용무;박상희
    • Journal of Broadcast Engineering
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    • v.2 no.1
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    • pp.74-83
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    • 1997
  • We have proposed a composite feature measure which combines the color and shape features of an image for image retrieval. We improved the performance of retrieval based on the efficient color quantization using the Lloyd-Max quanizer and on the Histogram matrix matching method which considers the spatial correlation of quantized color group. We also supplemented the color information using shape information with the Improved Moment Invarlants. We have tested our technique on Image database consisting of 200 actual trademark images. Our experimental results showed that our approach improved the performance compared to the previous method under the various situations such as rotation images, translation images, noise added images, gamma corrected images and so on. The efficiency of retrieval is found to be very high and experimental results are

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A Study of an Image Retrieval Method using Binary Subimage (이진 부분영상을 이용한 영상 검색 기법에 관한 연구)

  • 정순영;최민규;남재열
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.1
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    • pp.28-37
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    • 2001
  • An image retrieval method combining shape information of 2-dimension color histograms with color information of HSI color histograms is proposed in this paper. In addition, the proposed method can find location information of image through the comparison of similarity among subimages. The suggested retrieval method applies the location information to shape and color information and can retrieve region information which is hard to distinguish in the binary image. Some simulation results show that it works very well in the behalf of precision/recall graph compare with conventional method which uses color histogram. Especially, the proposed method brought well effects such as rotations and transitions of the objects in an image was found.

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