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author:

Chen, Y. (Chen, Y..) [1] | Zeng, X. (Zeng, X..) [2] | Chen, X. (Chen, X..) [3] | Guo, W. (Guo, W..) [4]

Indexed by:

Scopus

Abstract:

Automatic image annotation is a crucial area in computer vision, which plays a significant role in image retrieval, image description, and so on. Along with the internet technique developing, there are numerous images posted on the web, resulting in the fact that it is a challenge to annotate images only by humans. Hence, many computer vision researchers are interested in automatic image annotation and make a great effort in optimizing its performance. Automatic image annotation is a task that assigns several tags in a limited vocabulary to describe an image. There are many algorithms proposed to tackle this problem and all achieve great performance. In this paper, we review seven algorithms for automatic image annotation and evaluate these algorithms leveraging different image features, such as color histograms and Gist descriptor. Our goal is to provide insights into the automatic image annotation. A lot of comprehensive experiments, which are based on Corel5K, IAPR TC-12, and ESP Game datasets, are designed to compare the performance of these algorithms. We also compare the performance of traditional algorithms employing deep learning features. Considering that not all associated labels are annotated by human annotators, we leverage the DIA metrics on IAPR TC-12 and ESP Game datasets. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Keyword:

Computer vision; Image annotation; Image retrieval; Tag assignment

Community:

  • [ 1 ] [Chen, Y.]The College of Mathematics and Computer Science, Fuzhou University, Fujian, China
  • [ 2 ] [Zeng, X.]The College of Mathematics and Computer Science, Fuzhou University, Fujian, China
  • [ 3 ] [Chen, X.]The College of Mathematics and Computer Science, Fuzhou University, Fujian, China
  • [ 4 ] [Guo, W.]The College of Mathematics and Computer Science, Fuzhou University, Fujian, China

Reprint 's Address:

  • [Chen, X.]The College of Mathematics and Computer Science, Fuzhou University, The College of Mathematics and Computer Science, Fuzhou UniversityChina

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Source :

Applied Intelligence

ISSN: 0924-669X

Year: 2020

Issue: 10

Volume: 50

Page: 3412-3428

5 . 0 8 6

JCR@2020

3 . 4 0 0

JCR@2023

ESI HC Threshold:132

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 18

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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