arrow
Volume 13, Issue 3
A Salient Object-Based Image Retrieval Using Shape and Color Features

Shuxian Huang and Wenbing Chen

J. Info. Comput. Sci. , 13 (2018), pp. 201-211.

Export citation
  • 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.
  • AMS Subject Headings

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@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:
Copy to clipboard
The citation has been copied to your clipboard