A Salient Object-Based Image Retrieval Using Shape and Color Features
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@Article{JICS-13-201,
author = {Shuxian Huang and Wenbing Chen},
title = {A Salient Object-Based Image Retrieval Using Shape and Color Features},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {13},
number = {3},
pages = {201--211},
abstract = {Shuxian Huang, Wenbing Chen
Nanjing University of Information Science and Technology, Nanjing 210044, China
(Received January 17 2018, accepted July 05 2018)
In this paper, a salient object-based image retrieval method (SOBIR) is presented, which linearly
combines the shape and colour features of the salient objects contained in target and candidate images respectively to
carry out content-based image retrieval (CBIR). The framework of the proposed method is carried out as follows: first,
the mean shift and region growing algorithms are used to segment an input image into many regions; secondly, based
on these regional contrasts the saliency map, the binary image, and the salient object image are extracted respectively;
thirdly, the shape representation of the salient object is extracted from the binary image using an improved polar
Fourier Descriptor method, meanwhile the salient object contained in the input image is converted into a representation
of its histogram in the L∗a∗b∗ colour space; Finally, the similarity between the two salient objects contained in the
target and candidate images is defined by linearly combining both the shape and colour representations. Experimental
results show that, compared to the latest two CBIR methods, the proposed SOBIR method exhibits an excellent
performance in precision, recall, flexibility and efficiency.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22446.html}
}
TY - JOUR
T1 - A Salient Object-Based Image Retrieval Using Shape and Color Features
AU - Shuxian Huang and Wenbing Chen
JO - Journal of Information and Computing Science
VL - 3
SP - 201
EP - 211
PY - 2024
DA - 2024/01
SN - 13
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22446.html
KW - Image retrieval
KW - salient object
KW - region
KW - shape
KW - object detection
KW - similarity measure.
AB - Shuxian Huang, Wenbing Chen
Nanjing University of Information Science and Technology, Nanjing 210044, China
(Received January 17 2018, accepted July 05 2018)
In this paper, a salient object-based image retrieval method (SOBIR) is presented, which linearly
combines the shape and colour features of the salient objects contained in target and candidate images respectively to
carry out content-based image retrieval (CBIR). The framework of the proposed method is carried out as follows: first,
the mean shift and region growing algorithms are used to segment an input image into many regions; secondly, based
on these regional contrasts the saliency map, the binary image, and the salient object image are extracted respectively;
thirdly, the shape representation of the salient object is extracted from the binary image using an improved polar
Fourier Descriptor method, meanwhile the salient object contained in the input image is converted into a representation
of its histogram in the L∗a∗b∗ colour space; Finally, the similarity between the two salient objects contained in the
target and candidate images is defined by linearly combining both the shape and colour representations. Experimental
results show that, compared to the latest two CBIR methods, the proposed SOBIR method exhibits an excellent
performance in precision, recall, flexibility and efficiency.
Shuxian Huang and Wenbing Chen. (2024). A Salient Object-Based Image Retrieval Using Shape and Color Features.
Journal of Information and Computing Science. 13 (3).
201-211.
doi:
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