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.