CAJ | 학술논문

直线特征的检测是计算机视觉与图像处理的基本任务之一.主特征直线是图像中最显著而且被人们最为关心的一些直线.本文提出了从图像中自动检测主特征直线的算法.首先利用图像分割算法分析得到图像的特征边缘,然后用短线段逼近这些边缘像素,接着用动态聚类算法对这些线段进行聚类,并用直线拟合聚类中的线段得到所有可能存在的直线,最后根据直线有效性度量找到其中有效性最高的直线就是主特征直线.最后本文给出了主特征直线在图像自动修复和自动美学构图中的应用实例.
직선특정적검측시계산궤시각여도상처리적기본임무지일.주특정직선시도상중최현저이차피인문최위관심적일사직선.본문제출료종도상중자동검측주특정직선적산법.수선이용도상분할산법분석득도도상적특정변연,연후용단선단핍근저사변연상소,접착용동태취류산법대저사선단진행취류,병용직선의합취류중적선단득도소유가능존재적직선,최후근거직선유효성도량조도기중유효성최고적직선취시주특정직선.최후본문급출료주특정직선재도상자동수복화자동미학구도중적응용실례.
The detection of linear feature is one of the most fundamental tasks in computer vision and image processing. Principal lines are the most visually prominent lines in the images that people mostly care for. This paper presents a novel algorithm for automatic detection of the principal lines in digital images. The feature edge pixels are first detected from the image with an image segmentation technique. Then they are approximated with short line segments, which are further clustered using some similarity metric. Each cluster of segments is fitted with a straight line in an iterative manner. The principal lines are determined according to the validity measurement. We demonstrate two practical applications including automatic image recovering and automatic photo composition to show the applicability of the principal lines in image processing.