深度图像作为Kinect传感器的重要组成部分, 其获得的深度图像往往伴随着不可避免和无法预知的阴影噪声, 这也极大地影响并制约其在三维可视化等方面的应用及研究。因此, 针对深度图像提出了一种基于分数阶微分的阴影检测方法。在研究分数阶微分定义的Tiansi模板基础上, 设计并实现了一种非线性拉伸算子。该算子在0.6阶次可以增强阴影区域边界信息的同时实现阴影的有效检测。通过分析比较发现, 该方法在F测度的评价体系中可以达到0.971, 而其他传统的检测方法均小于0.7。实验结果证明文中提出方法可以有效实现深度图像的阴影检测。

As an essential component of the Kinect sensor, depth image always contains inevitable and unpredictable shadow noises which limit their usability in many 3D vision applications. Therefore, a shadow detection method based on fractional differential was proposed for depth image. Based on the study of Tiansi template defined by fractional differential, a non-linear stretching operator was designed and implemented. This operator can enhance the boundaries information of shadow regions significantly and accomplish the shadow detection effectively at 0.6 order. Compared with other traditional methods, the proposed method can reach up to 0.971 for F-measure, while the other methods were all less than 0.7. The experimental results indicate that the new method can detect shadow noises effectively.