Rong Duan1, Junshan Tan1, *, Jiaohua Qin1, Xuyu Xiang1, Yun Tan1, Neal N. Xiong2
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2335-2350, 2020, DOI:10.32604/cmc.2020.012161
Abstract In recent years, with the massive growth of image data, how to match the
image required by users quickly and efficiently becomes a challenge. Compared with
single-view feature, multi-view feature is more accurate to describe image information.
The advantages of hash method in reducing data storage and improving efficiency also
make us study how to effectively apply to large-scale image retrieval. In this paper, a
hash algorithm of multi-index image retrieval based on multi-view feature coding is
proposed. By learning the data correlation between different views, this algorithm uses
multi-view data with deeper level image semantics to achieve better retrieval… More >
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