R.V.V. Krishna1,*, S. Srinivas Kumar2
Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 281-290, 2020, DOI:10.31209/2019.100000121
Abstract In this paper, a color image segmentation algorithm is proposed by extracting
both texture and color features and applying them to the one -against-all multi
class support vector machine (MSVM) classifier for segmentation. Local Binary
Pattern is used for extracting the textural features and L*a*b color model is
used for obtaining the color features. The MSVM is trained using the samples
obtained from a novel soft rough fuzzy c-means (SRFCM) clustering. The fuzzy
set based membership functions capably handle the problem of overlapping
clusters. The lower and upper approximation concepts of rough sets deal well
with uncertainty, vagueness, and incompleteness… More >
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