Title :
New Fuzzy Texture Features for Robust Detection of Moving Objects
Author :
Chiranjeevi, P. ; Sengupta, S.
Author_Institution :
Dept. of Electron. & Electr. Commun. Eng., Indian Inst. of Technol. Kharagpur, Kharagpur, India
Abstract :
Robust detection of moving objects in presence of dynamic backgrounds is yet a challenging problem. In this letter, we propose a fuzzy membership transformation to be applied on the co-occurrence vector to derive a rich fuzzy transformed co-occurrence vector with shared membership values in a reduced dimensionality vector space. Fuzzy statistical texture features, derived from this fuzzy transformed co-occurrence vector, are able to improve the robustness in detecting moving objects, as compared to the traditional statistical texture features and other contemporary moving object segmentation approaches.
Keywords :
fuzzy set theory; image segmentation; image texture; object detection; statistical analysis; contemporary moving object segmentation; fuzzy membership transformation; fuzzy statistical texture features; fuzzy texture features; fuzzy transformed co-occurrence vector; moving objects robust detection; reduced dimensionality vector space; statistical texture features; Clustering algorithms; Feature extraction; Kernel; Object detection; Robustness; Vectors; Video sequences; Background subtraction; co-occurrence matrix; fuzzy co-occurrence vector; fuzzy integral; fuzzy statistical texture features; kernel fuzzy ${rm c}$-mean algorithm;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2012.2205380