An architecture for and query processing in distributed content-based image retrieval

被引:4
|
作者
Gudivada, VN [1 ]
Jung, GS [1 ]
机构
[1] JACKSON STATE UNIV,DEPT COMP SCI,JACKSON,MS 39217
关键词
D O I
10.1006/rtim.1996.0014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Images are being generated at an ever increasing rate by diverse military and civilian sources. A content-based image retrieval system is required to utilize information from the image repositories effectively. Content-based retrieval is characterized by several generic query classes. With the existence of the information superhighway, image repositories are evolving in a decentralized fashion on the Internet. This necessitates network transparent distributed access in addition to the content-based retrieval capability. Images stored in low-level formats such as vector and raster are referred to as physical images. Constructing interactive responses to user queries using physical images is not practical and robust. To overcome this problem, we introduce the notion of logical features and describe various features to enable content-based query processing in a distributed environment. We describe a tool named SemCap for extracting the logical features semi-automatically, We also propose an architecture and an application level communication protocol for distributed content-based retrieval. We describe the prototype implementation of the architecture and demonstrate its versatility on two distributed image collections. (C) 1996 Academic Press Limited
引用
收藏
页码:139 / 152
页数:14
相关论文
共 50 条
  • [1] Approximate query processing for a content-based image retrieval method
    Kwan, PWH
    Toraichi, K
    Kitagawa, H
    Kameyama, K
    [J]. DATABASE AND EXPERT SYSTEMS APPLICATIONS, PROCEEDINGS, 2003, 2736 : 517 - 526
  • [2] Query Classification in Content-Based Image Retrieval
    Markov, Ilya
    Vassilieva, Natalia
    [J]. DATABASES AND INFORMATION SYSTEMS V, 2009, 187 : 281 - +
  • [3] Query by fax for content-based image retrieval
    Fauzi, MFA
    Lewis, PH
    [J]. IMAGE AND VIDEO RETRIEVAL, 2002, 2383 : 91 - 99
  • [4] Approximate query processing for efficient content-based image retrieval based on a hierarchical SOM
    Yu, ZhiWen
    Wong, Hau-San
    [J]. 2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10, 2006, : 4013 - +
  • [5] Automatic Query Image Disambiguation for Content-based Image Retrieval
    Barz, Bjoern
    Denzler, Joachim
    [J]. PROCEEDINGS OF THE 13TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2018), VOL 5: VISAPP, 2018, : 249 - 256
  • [6] Adaptive query shifting for content-based image retrieval
    Giacinto, G
    Roli, F
    Fumera, G
    [J]. MACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION, 2001, 2123 : 337 - 346
  • [7] Automatic query generation for content-based image retrieval
    Breiteneder, C
    Eidenberger, H
    [J]. 2000 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, PROCEEDINGS VOLS I-III, 2000, : 705 - 708
  • [8] Query understanding in content-based image retrieval context
    Naud, Emilie
    Idrissi, Khalid
    Tellez, Bruno
    [J]. 2007 INTERNATIONAL WORKSHOP ON CONTENT-BASED MULTIMEDIA INDEXING, PROCEEDINGS, 2007, : 323 - +
  • [9] QUERY BY VISUAL EXAMPLE - CONTENT-BASED IMAGE RETRIEVAL
    HIRATA, K
    KATO, T
    [J]. LECTURE NOTES IN COMPUTER SCIENCE, 1992, 580 : 56 - 71
  • [10] A probabilistic architecture for content-based image retrieval
    Vasconcelos, N
    Lippman, A
    [J]. IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, VOL I, 2000, : 216 - 221