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 More >
Login
Register
