• 제목/요약/키워드: Image database

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BADA-$IV/I^2R$: Design & Implementation of an Efficient Content-based Image Retrieval System using a High-Dimensional Image Index Structure (바다-$IV/I^2R$: 고차원 이미지 색인 구조를 이용한 효율적인 내용 기반 이미지 검색 시스템의 설계와 구현)

  • Kim, Yeong-Gyun;Lee, Jang-Seon;Lee, Hun-Sun;Kim, Wan-Seok;Kim, Myeong-Jun
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.2S
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    • pp.678-691
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    • 2000
  • A variety of multimedia applications require multimedia database management systems to manage multimedia data, such as text, image, and video, as well as t support content-based image or video retrieval. In this paper we design and implement a content-based image retrieval system, BADA-IV/I$^2$R(Image Information Retrieval), which is developed based on BADA-IV multimedia database management system. In this system image databases can be efficiently constructed and retrieved with the visual features, such as color, shape, and texture, of image. we extend SQL statements to define image query based on both annotations and visual features of image together. A high-dimensional index structure, called CIR-tree, is also employed in the system to provide an efficient access method to image databases. We show that BADA-IV/I$^2$R provides a flexible way to define query for image retrieval and retrieves image data fast and effectively: the effectiveness and performance of image retrieval are shown by BEP(Bull's Eye Performance) that is used to measure the retrieval effectiveness in MPEG-7 and comparing the performance of CIR-tree with those of X-tree and TV-tree, respectively.

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Mobile Camera-Based Positioning Method by Applying Landmark Corner Extraction (랜드마크 코너 추출을 적용한 모바일 카메라 기반 위치결정 기법)

  • Yoo Jin Lee;Wansang Yoon;Sooahm Rhee
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1309-1320
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    • 2023
  • The technological development and popularization of mobile devices have developed so that users can check their location anywhere and use the Internet. However, in the case of indoors, the Internet can be used smoothly, but the global positioning system (GPS) function is difficult to use. There is an increasing need to provide real-time location information in shaded areas where GPS is not received, such as department stores, museums, conference halls, schools, and tunnels, which are indoor public places. Accordingly, research on the recent indoor positioning technology based on light detection and ranging (LiDAR) equipment is increasing to build a landmark database. Focusing on the accessibility of building a landmark database, this study attempted to develop a technique for estimating the user's location by using a single image taken of a landmark based on a mobile device and the landmark database information constructed in advance. First, a landmark database was constructed. In order to estimate the user's location only with the mobile image photographing the landmark, it is essential to detect the landmark from the mobile image, and to acquire the ground coordinates of the points with fixed characteristics from the detected landmark. In the second step, by applying the bag of words (BoW) image search technology, the landmark photographed by the mobile image among the landmark database was searched up to a similar 4th place. In the third step, one of the four candidate landmarks searched through the scale invariant feature transform (SIFT) feature point extraction technique and Homography random sample consensus(RANSAC) was selected, and at this time, filtering was performed once more based on the number of matching points through threshold setting. In the fourth step, the landmark image was projected onto the mobile image through the Homography matrix between the corresponding landmark and the mobile image to detect the area of the landmark and the corner. Finally, the user's location was estimated through the location estimation technique. As a result of analyzing the performance of the technology, the landmark search performance was measured to be about 86%. As a result of comparing the location estimation result with the user's actual ground coordinate, it was confirmed that it had a horizontal location accuracy of about 0.56 m, and it was confirmed that the user's location could be estimated with a mobile image by constructing a landmark database without separate expensive equipment.

Particle Filters using Gaussian Mixture Models for Vision-Based Navigation (영상 기반 항법을 위한 가우시안 혼합 모델 기반 파티클 필터)

  • Hong, Kyungwoo;Kim, Sungjoong;Bang, Hyochoong;Kim, Jin-Won;Seo, Ilwon;Pak, Chang-Ho
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.47 no.4
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    • pp.274-282
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    • 2019
  • Vision-based navigation of unmaned aerial vehicle is a significant technology that can reinforce the vulnerability of the widely used GPS/INS integrated navigation system. However, the existing image matching algorithms are not suitable for matching the aerial image with the database. For the reason, this paper proposes particle filters using Gaussian mixture models to deal with matching between aerial image and database for vision-based navigation. The particle filters estimate the position of the aircraft by comparing the correspondences of aerial image and database under the assumption of Gaussian mixture model. Finally, Monte Carlo simulation is presented to demonstrate performance of the proposed method.

Two-phase Content-based Image Retrieval Using the Clustering of Feature Vector (특징벡터의 끌러스터링 기법을 통한 2단계 내용기반 이미지검색 시스템)

  • 조정원;최병욱
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.3
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    • pp.171-180
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    • 2003
  • A content-based image retrieval(CBIR) system builds the image database using low-level features such as color, shape and texture and provides similar images that user wants to retrieve when the retrieval request occurs. What the user is interest in is a response time in consideration of the building time to build the index database and the response time to obtain the retrieval results from the query image. In a content-based image retrieval system, the similarity computing time comparing a query with images in database takes the most time in whole response time. In this paper, we propose the two-phase search method with the clustering technique of feature vector in order to minimize the similarity computing time. Experimental results show that this two-phase search method is 2-times faster than the conventional full-search method using original features of ail images in image database, while maintaining the same retrieval relevance as the conventional full-search method. And the proposed method is more effective as the number of images increases.

Design and Implementation of the Endoscope Image Store System in the Orthopedics (정형외과 관절경 영상 저장 시스템의 설계 및 구현)

  • 심갑식;정태영
    • Journal of the Korea Society of Computer and Information
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    • v.7 no.4
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    • pp.8-15
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    • 2002
  • This Paper proposes designing and implementing the database system storing the medical images. This system collects the medical image when doctors operate and diagnose the patients using the endoscope in the orthopedics, then stores the medical image data to database. Therefore. system avoids duplicated medical data, retrieves and updates the medical data effectively. The medical image data can be shared to the multiple users and application programs. This system consists of the five components. that is, the input module acquiring the medical image from the endoscope. the modulo storing the medical image. the database design and implementation storms the patient's disease history and the medical image data, user friendly interface design and implementation, and the simple data retrieval engine. The features of the system are followed. The image catcher program using DirectShow is portable any image catcher board And because the image catcher algorithm is implemented as a public module, The throughput can be increased during the development of video and audio contents on internet.

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Implementation of Image Retrieval System using Complex Image Features (복합적인 영상 특성을 이용한 영상 검색 시스템 구현)

  • 송석진;남기곤
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.8
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    • pp.1358-1364
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    • 2002
  • Presently, Multimedia data are increasing suddenly in broadcasting and internet fields. For retrieval of still images in multimedia database, content-based image retrieval system is implemented in this paper that user can retrieve similar objects from image database after choosing a wanted query region of object. As to extract color features from query image, we transform color to HSV with proposed method that similarity is obtained it through histogram intersection with database images after making histogram. Also, query image is transformed to gray image and induced to wavelet transformation by which spatial gray distribution and texture features are extracted using banded autocorrelogram and GLCM before having similarity values. And final similarity values is determined by adding two similarity values. In that, weight value is applied to each similarity value. We make up for defects by taking color image features but also gray image features from query image. Elevations of recall and precision are verified in experiment results.

A Hierarchical Image Mosaicing using Camera and Object Parameters for Efficient Video Database Construction (효율적인 비디오 데이터베이스 구축을 위해 카메라와 객체 파라미터를 이용한 계층형 영상 모자이크)

  • 신성윤;이양원
    • Journal of Korea Multimedia Society
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    • v.5 no.2
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    • pp.167-175
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    • 2002
  • Image Mosaicing creates a new image by composing video frames or still images that are related, and performed by arrangement, composition and redundancy analysis of images. This paper proposes a hierarchical image mosaicing system using camera and object parameters far efficient video database construction. A tree-based image mosiacing has implemented for high-speed computation time and for construction of static and dynamic image mosaic. Camera parameters are measured by using least sum of squared difference and affine model. Dynamic object detection algorithm has proposed for extracting dynamic objects. For object extraction, difference image, macro block, region splitting and 4-split detection methods are proposed and used. Also, a dynamic positioning method is used for presenting dynamic objects and a blurring method is used for creating flexible mosaic image.

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A Multi-Stage Approach to Secure Digital Image Search over Public Cloud using Speeded-Up Robust Features (SURF) Algorithm

  • AL-Omari, Ahmad H.;Otair, Mohammed A.;Alzwahreh, Bayan N.
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.65-74
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    • 2021
  • Digital image processing and retrieving have increasingly become very popular on the Internet and getting more attention from various multimedia fields. That results in additional privacy requirements placed on efficient image matching techniques in various applications. Hence, several searching methods have been developed when confidential images are used in image matching between pairs of security agencies, most of these search methods either limited by its cost or precision. This study proposes a secure and efficient method that preserves image privacy and confidentially between two communicating parties. To retrieve an image, feature vector is extracted from the given query image, and then the similarities with the stored database images features vector are calculated to retrieve the matched images based on an indexing scheme and matching strategy. We used a secure content-based image retrieval features detector algorithm called Speeded-Up Robust Features (SURF) algorithm over public cloud to extract the features and the Honey Encryption algorithm. The purpose of using the encrypted images database is to provide an accurate searching through encrypted documents without needing decryption. Progress in this area helps protect the privacy of sensitive data stored on the cloud. The experimental results (conducted on a well-known image-set) show that the performance of the proposed methodology achieved a noticeable enhancement level in terms of precision, recall, F-Measure, and execution time.

A Feature-Based Retrieval Technique for Image Database (특징기반 영상 데이터베이스 검색 기법)

  • Kim, Bong-Gi;Oh, Hae-Seok
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.11
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    • pp.2776-2785
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    • 1998
  • An image retrieval system based on image content is a key issue for building and managing large multimedia database, such as art galleries and museums, trademarks and copyrights, and picture archiving and communication system. Therefore, the interest on the subject of content-based image retrieval has been greatly increased for the last few years. This paper proposes a feature-based image retrieval technique which uses a compound feature vector representing both of color and shape of an image. Color information for the feature vector is obtained using the algebraic moment of each pixel of an image based on the property of regional color distribution. Shape information for the feature vector is obtained using the Improved Moment Invariant(IMI) which reduces the quantity of computation and increases retrieval efficiency. In the preprocessing phase for extracting shape feature, we transform a color image into a gray image. Since we make use of the modified DCT algorithm, it is implemented easily and can extract contour in real time. As an experiment, we have compared our method with previous methods using a database consisting of 150 automobile images, and the results of the experiment have shown that our method has the better performance on retrieval effectiveness.

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An approach for improving the performance of the Content-Based Image Retrieval (CBIR)

  • Jeong, Inseong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.6_2
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    • pp.665-672
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    • 2012
  • Amid rapidly increasing imagery inputs and their volume in a remote sensing imagery database, Content-Based Image Retrieval (CBIR) is an effective tool to search for an image feature or image content of interest a user wants to retrieve. It seeks to capture salient features from a 'query' image, and then to locate other instances of image region having similar features elsewhere in the image database. For a CBIR approach that uses texture as a primary feature primitive, designing a texture descriptor to better represent image contents is a key to improve CBIR results. For this purpose, an extended feature vector combining the Gabor filter and co-occurrence histogram method is suggested and evaluated for quantitywise and qualitywise retrieval performance criterion. For the better CBIR performance, assessing similarity between high dimensional feature vectors is also a challenging issue. Therefore a number of distance metrics (i.e. L1 and L2 norm) is tried to measure closeness between two feature vectors, and its impact on retrieval result is analyzed. In this paper, experimental results are presented with several CBIR samples. The current results show that 1) the overall retrieval quantity and quality is improved by combining two types of feature vectors, 2) some feature is better retrieved by a specific feature vector, and 3) retrieval result quality (i.e. ranking of retrieved image tiles) is sensitive to an adopted similarity metric when the extended feature vector is employed.