An efficient image retrieval tool: query based image management system

被引:1
|
作者
Ahmad K. [1 ]
Sahu M. [2 ]
Shrivastava M. [3 ]
Rizvi M.A. [3 ]
Jain V. [4 ]
机构
[1] Department of CS & IT, Maulana Azad National Urdu University, Hyderabad
[2] Department of Computer Science, Govt. Polytechnic College, Dindori, MP
[3] Department of Computer Engineering and Applications, NITTTR, Bhopal, MP
[4] Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), Delhi
关键词
Content-based image retrieval (CBIR); Contrast; Energy; Entropy; Horizontal and vertical edges; Mean and standard deviation; Query-based image management system (QBIMS);
D O I
10.1007/s41870-018-0198-9
中图分类号
学科分类号
摘要
As the development over a computer is going up, many systems are under the process of development and several systems exist which are working for storage and retrieval of images based on their content of the image, these types of systems are called CBIR. It is comparatively costlier than an image indexing system, but more accurate too. Hence, this reveals that there exists a proportional relation between accurateness and the computational cost. This swapping reduces cost and more competent algorithms are introduced and increased computational power turns into inexpensive. In this paper, an honest effort is made to retrieve the closest image to the input by the user from the image database. In this newly designed system, all the images are stored in the database as in the form of a visual content matrix and matching is performed using that matrix. In query based image management system (QBIMS), the primary description of the image is given by its shape, texture, and color. The working principle behind QBIMS is completely different than that of indexing. This helps QBIMS to fetch the closest image from the digital image datasets. Through this proposed tool an attempt is made for the purpose of computing power increment as well as cost decrement of the whole system. The functionality of the system is described along with snapshots of the GUI of the developed tool. © 2018, Bharati Vidyapeeth's Institute of Computer Applications and Management.
引用
下载
收藏
页码:103 / 111
页数:8
相关论文
共 50 条
  • [21] RbQE: An Efficient Method for Content-Based Medical Image Retrieval Based on Query Expansion
    Metwally Rashad
    Ibrahem Afifi
    Mohammed Abdelfatah
    Journal of Digital Imaging, 2023, 36 : 1248 - 1261
  • [22] Approximate query processing for efficient content-based image retrieval based on a hierarchical SOM
    Yu, ZhiWen
    Wong, Hau-San
    2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10, 2006, : 4013 - +
  • [23] RbQE: An Efficient Method for Content-Based Medical Image Retrieval Based on Query Expansion
    Rashad, Metwally
    Afifi, Ibrahem
    Abdelfatah, Mohammed
    JOURNAL OF DIGITAL IMAGING, 2023, 36 (03) : 1248 - 1261
  • [24] DAIR: A Query-Efficient Decision-based Attack on Image Retrieval Systems
    Chen, Mingyang
    Lu, Junda
    Wang, Yi
    Qin, Jianbin
    Wang, Wei
    SIGIR '21 - PROCEEDINGS OF THE 44TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, 2021, : 1064 - 1073
  • [25] An efficient image retrieval system with structured query based feature selection and filtering initial level relevant images using range query
    Annrose, J.
    Christopher, C. Seldev
    OPTIK, 2018, 157 : 1053 - 1064
  • [26] Efficient Binary Coding for Subspace-based Query-by-Image Video Retrieval
    Xu, Ruicong
    Yang, Yang
    Shen, Fumin
    Xie, Ning
    Shen, Heng Tao
    PROCEEDINGS OF THE 2017 ACM MULTIMEDIA CONFERENCE (MM'17), 2017, : 1354 - 1362
  • [27] Ontological query language for content based image retrieval
    Town, C
    Sinclair, D
    IEEE WORKSHOP ON CONTENT-BASED ACCESS OF IMAGE AND VIDEO LIBRARIES, PROCEEDINGS, 2001, : 75 - 80
  • [28] Query Classification in Content-Based Image Retrieval
    Markov, Ilya
    Vassilieva, Natalia
    DATABASES AND INFORMATION SYSTEMS V, 2009, 187 : 281 - +
  • [29] Query by fax for content-based image retrieval
    Fauzi, MFA
    Lewis, PH
    IMAGE AND VIDEO RETRIEVAL, 2002, 2383 : 91 - 99
  • [30] Query expansion by text and image features in image retrieval
    Zhou, H
    Chan, SY
    Kok, FL
    JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 1998, 9 (04) : 287 - 299