A fuzzy segmentation of salient region of interest in low depth of field image

Authors:
KeDai Zhang;HanQing Lu;ZhenYu Wang;Qi Zhao;MiYi Duan
Affiliations:
National Laboratory of Pattern Recognition Institute of Automation, CAS;National Laboratory of Pattern Recognition Institute of Automation, CAS;National Laboratory of Pattern Recognition Institute of Automation, CAS;Beijing Graphics Institute, Beijing, China;Beijing Graphics Institute, Beijing, China
Venue:
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
Year:
2007

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Abstract

Unsupervised segmenting region of interest in images is very useful in content-based application such as image indexing for content-based retrieval and target recognition. The proposed method applies fuzzy theory to separate the salient region of interest from background in low depth of field (DOF) images automatically. First the image is divided into regions based on mean shift method and the regions are characterized by color features and wavelet modulus maxima edge point densities. And then the regions are described as fuzzy sets by fuzzification. The salient region interest and background are separated by defuzzification on fuzzy sets finally. The segmentation method is full automatic and without empirical parameters.