Progressive Query Based Search and Retrieval in Large Image Archives

被引：0
|
作者：
Lakshmi, D. Rajya [1 ]
Damodaram, A. [2 ]
Babu, B. Raveendra [3 ]
Lal, J. A. Chandu [4 ]
机构：
[1] ANITS Engg Coll Visakhapatnam, Visakhapatnam, Andhra Pradesh, India
[2] JNTU Coll Engn Hyderabad, Hyderabad, Andhra Pradesh, India
[3] RVR & JC Engn Coll Guntur, Guntur, India
[4] GITAM Univ Visakhapatnam, Visakhapatnam, Andhra Pradesh, India
来源：
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2007年 / 7卷 / 08期
关键词：
Progressive Searching; Content Based; Templates; DWT; Texture Analysis;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we describe the architecture and implementation of a framework to perform content based search of an image database, where content is specified by the user at one or more of the following three abstraction levels: pixel, feature, and semantic. Query based Image Acquisition System deals with query passing, query parsing, SQL query generation and image retrieval. The image is retrieved just based on the query given by the user. It provides a user friendly interface for user to pass his query. The required image is returned to the user based on his query by performing a search on the database. All this procedure is carried on in semantic level. This framework is well suited for searching scientific databases, such as satellite image, medical, and seismic data repositories, where the volume and diversity of the information do not allow the apriori generation of exhaustive indices, but we have successfully demonstrated its usefulness on still-image archives.
引用
收藏
页码：212 / 219
页数：8
相关论文
共 50 条
  • [21] An efficient image retrieval tool: query based image management system
    Ahmad K.
    Sahu M.
    Shrivastava M.
    Rizvi M.A.
    Jain V.
    International Journal of Information Technology, 2020, 12 (1) : 103 - 111
  • [22] Image retrieval: Color and texture combining based on query-image
    Markov, Ilya
    Vassilieva, Natalia
    IMAGE AND SIGNAL PROCESSING, 2008, 5099 : 430 - +
  • [23] Extracting Information from a Query Image, for Content Based Image Retrieval
    Gupta, Nitin
    Das, Sukhendu
    Chakraborti, Sutanu
    2015 EIGHTH INTERNATIONAL CONFERENCE ON ADVANCES IN PATTERN RECOGNITION (ICAPR), 2015, : 225 - +
  • [24] Adaptively filtering query results for large scale image feature retrieval
    Ai, Lie-Fu
    Yu, Jun-Qing
    Guan, Tao
    He, Yun-Feng
    Jisuanji Xuebao/Chinese Journal of Computers, 2015, 38 (01): : 122 - 132
  • [25] Conceptual Query Expansion and Visual Search Results Exploration for Web Image Retrieval
    Hoque, Enamul
    Strong, Grant
    Hoeber, Orland
    Gong, Minglun
    ADVANCES IN INTELLIGENT WEB MASTERING 3, 2011, 86 : 73 - 82
  • [26] KERNEL-BASED HASHING FOR CONTENT-BASED IMAGE RETRIEVAL IN LARGE REMOTE SENSING DATA ARCHIVES
    Demir, Beguem
    Bruzzone, Lorenzo
    2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2014, : 3542 - 3545
  • [27] An extensible query language for content based image retrieval based on lucene
    Pein, Raoul Pascal
    Lu, Joan
    Renz, Wolfgang
    2008 IEEE 8TH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY, VOLS 1 AND 2, 2008, : 179 - +
  • [28] An Efficient Multi Query System for Content Based Image Retrieval Using Query Replacement
    Vimina, E. R.
    Ramakrishnan, K.
    Nandakumar, Navya
    Jacob, Poulose K.
    2015 16TH IEEE/ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNPD), 2015, : 43 - 47
  • [29] Adaptive query shifting for content-based image retrieval
    Giacinto, G
    Roli, F
    Fumera, G
    MACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION, 2001, 2123 : 337 - 346
  • [30] Automatic query generation for content-based image retrieval
    Breiteneder, C
    Eidenberger, H
    2000 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, PROCEEDINGS VOLS I-III, 2000, : 705 - 708
12345