Invariant color model-based shadow removal in traffic image and a new metric for evaluating the performance of shadow removal methods

Authors:
Young Sung Soh;Hwanju Lee;Yakun Wang
Affiliations:
Dept. of Information Engineering, Myongji Univ., Yongin, Kyunggido, Korea;Dept. of Information Engineering, Myongji Univ., Yongin, Kyunggido, Korea;Dept. of Information Engineering, Myongji Univ., Yongin, Kyunggido, Korea
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

Citing 3
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Shadow identification and classification using invariant color models

ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03

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Abstract

To track objects in a traffic image sequence, objects must be extracted first. Background differencing is frequently used to extract objects. When objects are extracted, it is quite possible that shadows are included. With shadow it is not easy to do precise tracking. Thus shadows need to be removed. To do this, we proposed invariant color-based shadow removal method. Many shadow removal methods were proposed. To compare the quality of methods, several metrics were suggested. However, they suffer from inconsistency where qualitative and quantitative results do not coincide. In this paper, we proposed a new metric having such consistency.