Research on Image Network Retrieval Application Based on Swarm Optimization Algorithm

DOI

10.2991/ncce-18.2018.83How to use a DOI?

Keywords

Particle swarm algorithm, image, network retrieval, color extraction.

Abstract

The traditional image retrieval adopts a text-based method, which requires a lot of manual annotation of the images in the image library and matches according to the keywords when searching. Already not suitable for the modern image network retrieval, this paper proposes a network model based on the particle swarm optimization algorithm, and then establishes a mathematical model based on swarm intelligence. Using images' low-level visual features to retrieve images is the core of content-based image retrieval. Content-based image retrieval is an approximate matching technique that combines computer vision, image processing, and database and other technical achievements in many fields. The feature extraction can be done automatically by computer, avoiding the subjectivity of traditional manual annotation, and can also improve the accuracy. degree

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qingpeng Nie
PY  - 2018/05
DA  - 2018/05
TI  - Research on Image Network Retrieval Application Based on Swarm Optimization Algorithm
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 524
EP  - 529
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.83
DO  - 10.2991/ncce-18.2018.83
ID  - Nie2018/05
ER  -