NDLI: New strategy for CBIR by combining low-level visual features with a colour descriptor

Content Provider	IET Digital Library
Author	Unar, Salahuddin Wang, Xingyuan Wang, Chunpeng Wang, Mingxu
Abstract	In computer vision, the analysis of image contents plays a significant role to perform intelligent tasks such as object recognition and image retrieval. These contents can be low-level visual features or colour information within an image. For content-based image retrieval (CBIR), several methods have been proposed that focus on either low-level visual features extraction or the colour information, and very few works can be seen that retrieve the images by fusing both types of contents. Consequently, this work addresses the problem of combining low-level visual features with colour information that helps to improve the retrieval accuracy of CBIR. The proposed strategy extracts the low-level visual salient features with features from accelerated segment test feature descriptor and quantises the salient keypoints into a feature vector. The colour information of the image is extracted and segmented with non-linear Lab* colour space and quantised into a feature vector. The similarity for both the feature vectors including visual and colour features is computed and combined together. The top-rank images are retrieved for the obtained feature vector using the distance metric. The experimental results on two standard benchmark datasets show the improved efficiency and 85% accuracy of the proposed strategy over state-of-the-art methods.
Starting Page	1191
Ending Page	1200
Page Count	10
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 7, May (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0098
Journal	IET Image Processing
Publisher Date	2019-03-26
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Accelerated Segment Test Feature Descriptor CBIR Colour Descriptor Colour Information Computer Vision Computer Vision And Image Processing Technique Content-based Image Retrieval Content-based Retrieval Feature Extraction Feature Vector Image Colour Analysis Image Contents Image Matching Image Recognition Image Representation Image Retrieval Image Segmentation Information Retrieval Technique Low-level Visual Feature Extraction Low-level Visual Salient Feature Object Recognition Optical, Image And Video Signal Processing Visual Colour Feature
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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