|Table of Contents|

Shadow Removal Algorithm by Combining Cross-correlationand Gradient Feature in Gray Sequence Images(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2019年02期
Page:
59-
Research Field:
计算机与信息工程
Publishing date:

Info

Title:
Shadow Removal Algorithm by Combining Cross-correlationand Gradient Feature in Gray Sequence Images
Author(s):
Liang Lei; Liu Huai; Liang Qinjia; Dong Chunyan
School of Electrical and Automation Engineering,Nanjing Normal University,Nanjing 210023,China
Keywords:
shadow removal; gray sequence images; gradient of grayscale ratio; normalized cross correlation(NCC)
PACS:
TP391
DOI:
10.3969/j.issn.1672-1292.2019.02.008
Abstract:
Moving shadows have adverse effects on the accuracy of the detected target while detecting moving target in video surveillance scene. In order to eliminate the interference of the moving shadows,a shadow removal algorithm is proposed by combining the four-direction gradient of the grayscale ratio and the feature of the normalized cross correlation(NCC)in this paper. Firstly,the grayscale ratio of the foreground pixel to its corresponding background pixel is calculated in gray sequence images. Secondly,because the grayscale ratio among a pixel’s neighborhood in shadow region has a small change,the calculated four-direction gradient mean can be applied to detect and remove shadow. Finally,in order to avoid that the moving target is removed as shadow and ensure the integrity of the detected target,the feature of the NCC is employed to keep the integrity of moving target because difference of correlation between the moving target and its corresponding background is much larger than that between shadow and its corresponding background. The qualitative and quantitative analysis of experimental results show that the algorithm presented in this paper is superior to other similar shadow removal algorithms in shadow removal ratio and keeping the integrity of the detected target.

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Last Update: 2019-06-30