深度图像中直线特征的提取

Linear Feature Extraction in Range Image

深度图像具有能够表征物体表面三维立体信息的优势,而直线则携带了图像中重要的结构信息,对图像分割、图像识别等后续图像分析具有十分重要的意义。提出一种新的深度图像直线检测方法,由直线组成的直线框架方法,能够精确地、综合地提取深度图像的直线特征。首先,在指定邻域内对每个深度像素估计表面法向量;通过对表面法向量的相关计算得到每个像素点的边缘强度;之后,通过全局匹配措施,连点成线;最后,采用Hough变换在深度图像上标记直线。通过仿真结果对比,不难发现相较于其他直线特征提取方法,本文提出的新方法能够提供更平滑干净的直线检测结果;此外,在折痕边缘处获得单条直线,阶跃边缘处获得两条平行直线,因而可作为深度图像的3D结构信息。

Compared with gray image,range image can show the surface information of3 Dobject.Lines,with important structural information in image,are essential to image analysis,such as image segmentation and image recognition.This paper proposes a new line detection method in range image.Line-frame which is composed of lines can precisely and comprehensively extract line feature,and fitness measure is used to evaluate the line-frame which is composed of lines.First and foremost,we estimate surface normal of every range pixel in specific neighborhood.Then,the surface normal is calculated to represent edge strength.Secondly,we connect points to be lines in the way of fitness measure.Finally,lines are marked by Hough transform in range image.Compared with other line feature extraction methods,the proposed method can provide line detection result which is smoother and cleaner.In addition,a single line is gained in the place of crease edge,while two parallel lines are gained in the place of jump edge,which can be3 Dstructural information of range image.