An Adaptive Shadow Detection Algorithm Using Edge Texture and Sampling Deduction

doi:10.7652/xjtuxb201302007

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An Adaptive Shadow Detection Algorithm Using Edge Texture and Sampling Deduction

更新时间：2025-07-09

- An Adaptive Shadow Detection Algorithm Using Edge Texture and Sampling Deduction
- Vol. 47, Issue 2, Pages: 39-46(2013)
- 作者机构：
  
  第二炮兵工程大学502教研室,西安,710025
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201302007
  CLC： TP391
- Online First：10 February 2013，
  
  Published：2013
- 稿件说明：
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An Adaptive Shadow Detection Algorithm Using Edge Texture and Sampling Deduction[J]. 2013, 47(2): 39-46.
DOI：

An Adaptive Shadow Detection Algorithm Using Edge Texture and Sampling Deduction[J]. 2013, 47(2): 39-46. DOI： 10.7652/xjtuxb201302007.

摘要

为改进阴影检测的准确度和场景自适应能力

提高运动目标检测精度

设计了一种自适应的阴影检测算法。该算法利用候选前景与原始背景的Y、U、V分量变化比率来检测阴影像素

并结合全局边缘纹理特征及抽样推断方法来估计检测阈值。算法能自动完成阈值估计及阴影判别过程而无需人工干预

并可自动适应各种光线条件

具有较强的鲁棒性。对不同光线环境的标准视频检测实验表明

该算法在精度和实时性上均有所提升

阴影检测综合性能指标达到了94%以上。

Abstract

An adaptive shadow detection algorithm is proposed to improve the accuracy and scene adaptive capacity of the shadow detection and to raise the effect of moving object detection. The change ratios of YUV components between candidate foreground and original background are used to detect shadow pixels

and the global edge texture and sampling deduction methods are employed to estimate the detection threshold values. The algorithm automatically complete the processes of both thresholds estimation and shadow discriminant without any manual intervention

so the algorithm is adaptive to different light conditions and has a strong robustness. Experiment results on standard videos with different lighting conditions show that both the accuracy and stability are raised by the proposed algorithm and the average comprehensive index of the proposed algorithm can reach more than 94%.

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references

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刘宏, 李锦涛, 刘群, 等. 融合颜色和梯度特征的运动阴影消除方法 [J]. 计算机辅助设计与图形学学报, 2007, 19(10): 1279-1285.

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