Moving vehicles'''' shadow detection with fast normalized cross-correlation
基于快速归一化互相关函数的运动车辆阴影检测算法

Video detection plays an important role in intelligent transportation system,and the shadows of moving vehicles have serious influence on object detection and segmentation.By adopting a FNCC(Fast Normalized Cross-Correlation) algorithm in this paper,moving shadows were directly detected from grayscale video sequences.By applying three sum-tables in FNCC and detecting shadows within a confined range,the computational complexity had been significantly reduced compared with the traditional NCC(Normalized Cross-Correlation) algorithm.And the experimental results have shown that this method can detect moving vehicles' shadows efficiently and accurately.