Object Detection using Multiple Color Normalization and Moving Color Information 


Vol. 12,  No. 7, pp. 721-728, Dec.  2005
10.3745/KIPSTB.2005.12.7.721


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  Abstract

This paper suggests effective object detection system for moving objects with specified color and motion information. The proposed detection system includes the object extraction and definition process which uses MCN(Multiple Color Normalization) and MCWUPC(Moving Color Weighted Unmatched Pixel Count) computation to decide the existence of moving object and object segmentation technique using signature information is used to exactly extract the objects with high probability. Finally, real time detection system is implemented to verify the effectiveness of the technique and experiments show that the success rate of object tracking is more than 89% of total 120 image frames.

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[IEEE Style]

S. H. Kim, "Object Detection using Multiple Color Normalization and Moving Color Information," The KIPS Transactions:PartB , vol. 12, no. 7, pp. 721-728, 2005. DOI: 10.3745/KIPSTB.2005.12.7.721.

[ACM Style]

Sang Hoon Kim. 2005. Object Detection using Multiple Color Normalization and Moving Color Information. The KIPS Transactions:PartB , 12, 7, (2005), 721-728. DOI: 10.3745/KIPSTB.2005.12.7.721.

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