Title :
A novel workspace for image clustering
Author :
Krinidis, Michail ; Krinidis, Stelios ; Chatzis, Vassilios
Author_Institution :
Inf. Manage. Dept., Technol. Inst. of Kavala, Kavala, Greece
Abstract :
A novel image clustering method based on the image histogram, which is processed by the empirical mode decomposition (EMD) is presented. An intermediate step derived from the EMD, which can decompose any nonlinear and non-stationary data into a number of intrinsic mode functions (IMFs) is exploited. The IMFs of the image histogram have interesting characteristics and provide a novel workspace that is utilized in order to automatically detect the different clusters into the image under examination. The proposed method was applied to several real and synthetic images and the obtained results show good image clustering robustness.
Keywords :
pattern clustering; EMD; IMF; empirical mode decomposition; image clustering; image histogram; intrinsic mode functions; nonstationary data; Clustering algorithms; Clustering methods; Data mining; Histograms; Image segmentation; Partitioning algorithms; White noise; Image clustering; empirical mode decomposition; intrinsic mode functions; segmentation;
Conference_Titel :
Digital Signal Processing (DSP), 2011 17th International Conference on
Conference_Location :
Corfu
Print_ISBN :
978-1-4577-0273-0
DOI :
10.1109/ICDSP.2011.6004884