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A Bidirectional Adaptive Bandwidth Mean Shift Strategy for Clustering
The bandwidth of a kernel function is a crucial parameter in the mean shift
algorithm. This paper proposes a novel adaptive bandwidth strategy which
contains three main contributions. (1) The differences among different adaptive
bandwidth are analyzed. (2) A new mean shift vector based on bidirectional
adaptive bandwidth is defined, which combines the advantages of different
adaptive bandwidth strategies. (3) A bidirectional adaptive bandwidth mean
shift (BAMS) strategy is proposed to improve the ability to escape from the
local maximum density. Compared with contemporary adaptive bandwidth mean shift
strategies, experiments demonstrate the effectiveness of the proposed strategy.Comment: Accepted by ICIP 201