针对室内场景深度图像,检测场景中的面片边缘信息并确定场景中的完整面信息是实现室内场景分析和理解的基础.基于深度信息局部二值模式特征,提出一种室内场景深度图像边缘检测的方法.首先对场景深度信息图分别求X方向和Y方向的梯度信息,结合2个梯度图找到深度信息图的基本边缘信息;然后计算基本边缘附近的局部二值模式特征信息,并计算深度图每个点的法线信息;最后利用深度信息局部二值模式特征和法线信息对边缘信息进行判断和矫正,以提取深度图像的面片边缘信息.实验结果表明,该方法能够高效、准确地检测室内场景深度图像的边缘信息,避免边缘信息的过检测和欠检测.%To detect the edge information and extract whole planes in the input indoor scene RGB-D images is an important and fundamental issue for scene analysis and understanding. This paper presents a novel edge de-tection method by using the local binary pattern features computed on scene deep images. First, the gradient information alongX-direction andY-direction are calculated in the scene deep map and the basic edge informa-tion can thus be detected using these two gradient maps. Then, the local binary pattern features nearby the basic edges can be computed and the normal information of the indoor scene point cloud can also be calculated. Fi-nally, combining the local binary pattern features and the normal information, we can adjust and extract the edge information in the indoor scene. Experimental results illustrate that our proposed approach can effectively detect the edge information of indoor scenes, and also avoid the over-detection and under-detection during edge extraction.
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