• Title/Summary/Keyword: Content-based Image Retrieval

Search Result 317, Processing Time 0.448 seconds

Content-based Image Retrieval using Color Ratio and Moment of Object Region (객체영역의 컬러비와 모멘트를 이용한 내용기반 영상검색)

  • Kim, Eun-Kyong;Oh, Jun-Taek;Kim, Wook-Hyun
    • The KIPS Transactions:PartB
    • /
    • v.9B no.4
    • /
    • pp.501-508
    • /
    • 2002
  • In this paper, we propose a content-based image retrieval using the color ratio and moment of object region. We acquire an optimal spatial information by the region splitting that utilizes horizontal-vertical projection and dominant color. It is based on hypothesis that an object locates in the center of image. We use color ratio and moment as feature informations. Those are extracted from the splitted regions and have the invariant property for various transformation, and besides, similarity measure utilizes a modified histogram intersection to acquire correlation information between bins in a color histogram. In experimental results, the proposed method shows more flexible and efficient performance than existing methods based on region splitting.

A Study on Increasing the Efficiency of Image Search Using Image Attribute in the area of content-Based Image Retrieval (내용기반 이미지 검색에 있어 이미지 속성정보를 활용한 검색 효율성 향상)

  • Mo, Yeong-Il;Lee, Cheol-Gyu
    • Journal of the Korea Society for Simulation
    • /
    • v.18 no.2
    • /
    • pp.39-48
    • /
    • 2009
  • This study reviews the limit of image search by considering on the image search methods related to content-based image retrieval and suggests a user interface for more efficient content-based image retrieval and the ways to utilize image properties. For now, most studies on image search are being performed focusing on content-based image retrieval; they try to search based on the image's colors, texture, shapes, and the overall form of the image. However, the results are not satisfactory because there are various technological limits. Accordingly, this study suggests a new retrieval system which adapts content-based image retrieval and the conventional keyword search method. This is about a way to attribute properties to images using texts and a fast way to search images by expressing the attribute of images as keywords and utilizing them to search images. Also, the study focuses on a simulation for a user interface to make query language on the Internet and a search for clothes in an online shopping mall as an application of the retrieval system based on image attribute. This study will contribute to adding a new purchase pattern in online shopping malls and to the development of the area of similar image search.

  • PDF

Design and Implementation of the Content-Based Image Retrieval System using Color Features on the World Wide Web (WWW에서 칼라특징을 이용한 내용기반 화상검색 시스템의 설계 및 구현)

  • Choi, Hyun-Sub;Choi, Ki-Ho
    • The Transactions of the Korea Information Processing Society
    • /
    • v.4 no.9
    • /
    • pp.2315-2332
    • /
    • 1997
  • In this paper, we implement a content based image retrieval system for image searching by visual features from the image databases on WWW (world wide web). The image retrieval system finds the images that contain the most similar color regions after the system automatically extracts color features from the input image. We can select one of two query methods which use a full image of $4{\times}4$ 16 sketched color region. The image similarity is calculated on the histogram intersection distance and the histogram Euclidean distance. As the experimental results show that the two different query types provide the precision/recall 0.84/0.92 and 0.85/0.93 respectively, this retrieval system has been able to obtain high performance and validity.

  • PDF

Using Context Information to Improve Retrieval Accuracy in Content-Based Image Retrieval Systems

  • Hejazi, Mahmoud R.;Woo, Woon-Tack;Ho, Yo-Sung
    • 한국HCI학회:학술대회논문집
    • /
    • /
    • pp.926-930
    • /
    • 2006
  • Current image retrieval techniques have shortcomings that make it difficult to search for images based on a semantic understanding of what the image is about. Since an image is normally associated with multiple contexts (e.g. when and where a picture was taken,) the knowledge of these contexts can enhance the quantity of semantic understanding of an image. In this paper, we present a context-aware image retrieval system, which uses the context information to infer a kind of metadata for the captured images as well as images in different collections and databases. Experimental results show that using these kinds of information can not only significantly increase the retrieval accuracy in conventional content-based image retrieval systems but decrease the problems arise by manual annotation in text-based image retrieval systems as well.

  • PDF

The Design an Implementation of Content-based Image Retrieval System Using Color Features (칼라 특징을 이용한 내용기반 화상검색시스템의 설계 및 구현)

  • 정원일;박정찬;최기호
    • Journal of the Korean Institute of Telematics and Electronics B
    • /
    • v.33B no.6
    • /
    • pp.111-118
    • /
    • 1996
  • A content-based image retrieval system is designed and implemetned using the color featurees which are histogram intersection and color pairs. The preprocessor for the image retrieval manage linearly the existing HSI(hue, saturation, saturation, intensity). Hue and intensity histogram thresholding for each color attribute is performed to split the chromatic and achromatic regions respectively. Grouping te indexes produced by the histogram intersection is used to save the retrieval times. Each image is divided into the cells of 32$\times$32 pixels, and color pairs are used to represent the query during retrievals. The recall/precision of histogram intersection is 0.621/0.663 and recall/precision of color pairs is 0.438/0.536. And recall/precision of proposed method is 0.765/0.775/. It is shown that the proposed method using histogram intersection and color pairs improves the retrieval rates.

  • PDF

Content-based Image Retrieval using Color Correlogram from a Segmented Image (분할된 영상에서의 칼라 코렐로그램을 이용한 내용기반 영상검색)

  • An, Myung-Seok;Cho, Seok-Je
    • Journal of KIISE:Computer Systems and Theory
    • /
    • v.28 no.10
    • /
    • pp.507-512
    • /
    • 2001
  • Recently, there has been studied on feature extraction method for efficient content-based image retrieval. Especially, many researchers have been studying on extracting from color information, because of its advantages. This paper proposes a feature and its extraction method based on color information in an image. The proposed method is computed from the image segmented into two parts: the complex part and the plan part. Our experiments show that the performance of the proposed method is better as compared with the original color correlogram method.

  • PDF

Effective Content-Based Image Retrieval Using Relevance feedback (관련성 피드백을 이용한 효과적인 내용기반 영상검색)

  • 손재곤;김남철
    • Proceedings of the IEEK Conference
    • /
    • /
    • pp.669-672
    • /
    • 2001
  • We propose an efficient algorithm for an interactive content-based image retrieval using relevance feedback. In the proposed algorithm, a new query feature vector first is yielded from the average feature vector of the relevant images that is fed back from the result images of the previous retrieval. Each component weight of a feature vector is computed from an inverse of standard deviation for each component of the relevant images. The updated feature vector of the query and the component weights are used in the iterative retrieval process. In addition, the irrelevant images are excluded from object images in the next iteration to obtain additional performance improvement. In order to evaluate the retrieval performance of the proposed method, we experiment for three image databases, that is, Corel, Vistex, and Ultra databases. We have chosen wavelet moments, BDIP and BVLC, and MFS as features representing the visual content of an image. The experimental results show that the proposed method yields large precision improvement.

  • PDF

Content-based Image Retrieval using an Improved Chain Code and Hidden Markov Model (개선된 chain code와 HMM을 이용한 내용기반 영상검색)

  • 조완현;이승희;박순영;박종현
    • Proceedings of the IEEK Conference
    • /
    • /
    • pp.375-378
    • /
    • 2000
  • In this paper, we propose a novo] content-based image retrieval system using both Hidden Markov Model(HMM) and an improved chain code. The Gaussian Mixture Model(GMM) is applied to statistically model a color information of the image, and Deterministic Annealing EM(DAEM) algorithm is employed to estimate the parameters of GMM. This result is used to segment the given image. We use an improved chain code, which is invariant to rotation, translation and scale, to extract the feature vectors of the shape for each image in the database. These are stored together in the database with each HMM whose parameters (A, B, $\pi$) are estimated by Baum-Welch algorithm. With respect to feature vector obtained in the same way from the query image, a occurring probability of each image is computed by using the forward algorithm of HMM. We use these probabilities for the image retrieval and present the highest similarity images based on these probabilities.

  • PDF