A novel fusion approach in the extraction of kernel descriptor with improved effectiveness and efficiency

Image representation using feature descriptors is crucial. A number of histogram-based descriptors are widely used for this purpose. However, histogram-based descriptors have certain limitations and kernel descriptors (KDES) are proven to overcome them. Moreover, the combination of more than one KDE...

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Published in:Multimedia tools and applications 2021-04, Vol.80 (10), p.14545-14564
Main Authors: Karmakar, Priyabrata, Teng, Shyh Wei, Lu, Guojun, Zhang, Dengsheng
Format: Article
Language:English
Subjects:
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Deep learning
Efficiency
Feature extraction
Histograms
Image retrieval
Kernels
Multimedia
Multimedia Information Systems
Special Purpose and Application-Based Systems
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cited_by cdi_FETCH-LOGICAL-c363t-e45f4f9fe3943bef57a1445350b29d3cb21e0dc56e6ab17b5f903a2748a717053
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container_title Multimedia tools and applications
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creator Karmakar, Priyabrata
Teng, Shyh Wei
Lu, Guojun
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description Image representation using feature descriptors is crucial. A number of histogram-based descriptors are widely used for this purpose. However, histogram-based descriptors have certain limitations and kernel descriptors (KDES) are proven to overcome them. Moreover, the combination of more than one KDES performs better than an individual KDES. Conventionally, KDES fusion is performed by concatenating them after the gradient, colour and shape descriptors have been extracted. This approach has limitations in regard to the efficiency as well as the effectiveness. In this paper, we propose a novel approach to fuse different image features before the descriptor extraction, resulting in a compact descriptor which is efficient and effective. In addition, we have investigated the effect on the proposed descriptor when texture-based features are fused along with the conventionally used features. Our proposed descriptor is examined on two publicly available image databases and shown to provide outstanding performances.
doi_str_mv 10.1007/s11042-020-10300-1
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subjects Computer Communication Networks
Computer Science
Data Structures and Information Theory
Deep learning
Efficiency
Feature extraction
Histograms
Image retrieval
Kernels
Multimedia
Multimedia Information Systems
Special Purpose and Application-Based Systems
title A novel fusion approach in the extraction of kernel descriptor with improved effectiveness and efficiency
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