Title :
Detection of Moving Objects Using Multi-channel Kernel Fuzzy Correlogram Based Background Subtraction
Author :
Chiranjeevi, Pojala ; Sengupta, Sabyasachi
Author_Institution :
Dept. of Electron. & Electr. Commun. Eng., Indian Inst. of Technol., Kharagpur, Kharagpur, India
Abstract :
In this paper, we examine the suitability of correlogram for background subtraction, as a step towards moving object detection. Correlogram captures inter-pixel relationships in a region and is seen to be effective for modeling the dynamic backgrounds. A multi-channel correlogram is proposed using inter-channel and intra-channel correlograms to exploit full color information and the inter-pixel relations on the same color planes and across the planes. We thereafter derive a novel feature, termed multi-channel kernel fuzzy correlogram, composed by applying a fuzzy membership transformation over multi-channel correlogram. Multi-channel kernel fuzzy correlogram maps multi-channel correlogram into a reduced dimensionality space and is less sensitivity to noise. The approach handles multimodal distributions without using multiple models per pixel unlike traditional approaches. The approach does not require ideal background frames for background model initialization and can be initialized with moving objects also. Effectiveness of the proposed method is illustrated on different video sequences.
Keywords :
fuzzy set theory; image colour analysis; image motion analysis; image sequences; object detection; video signal processing; background model initialization; color planes; dimensionality space; full color information; fuzzy membership transformation; inter-channel correlograms; inter-pixel relationships; intra-channel correlograms; moving object detection; multichannel correlogram; multichannel kernel fuzzy correlogram based background subtraction; multimodal distribution; video sequences; Clustering algorithms; Color; Computational modeling; Current measurement; Image color analysis; Kernel; Vectors; Background subtraction; fuzzy distance measure; inter-channel correlogram; kernel fuzzy c-mean algorithm; multi-channel correlogram; multi-channel kernel fuzzy correlogram;
Journal_Title :
Cybernetics, IEEE Transactions on
DOI :
10.1109/TCYB.2013.2274330