Title :
Detecting Wide Lines Using Isotropic Nonlinear Filtering
Author :
Liu, Laura ; Zhang, David ; You, Jane
Author_Institution :
Biometric Res. Centre, Hong Kong Polytech. Univ., Kowloon
fDate :
6/1/2007 12:00:00 AM
Abstract :
Lines provide important information in images, and line detection is crucial in many applications. However, most of the existing algorithms focus only on the extraction of line positions, ignoring line thickness. This paper presents a novel wide line detector using an isotropic nonlinear filter. Unlike most existing edge and line detectors which use directional derivatives, our proposed wide line detector applies a nonlinear filter to extract a line completely without any derivative. The detector is based on the isotropic responses via circular masks. A general scheme for the analysis of the robustness of the proposed wide line detector is introduced and the dynamic selection of parameters is developed. In addition, this paper investigates the relationship between the size of circular masks and the width of detected lines. A sequence of tests has been conducted on a variety of image samples and our experimental results demonstrate the feasibility and effectiveness of the proposed method
Keywords :
edge detection; feature extraction; image sampling; nonlinear filters; circular masks; directional derivatives; edge detection; image samples; isotropic nonlinear filtering; wide line detection; Data mining; Detectors; Feature extraction; Image analysis; Image edge detection; Information filtering; Information filters; Nonlinear filters; Robustness; Testing; Curvilinear structures; feature extraction; isotropic nonlinear filter; line detection; wide line detector; Algorithms; Anisotropy; Artificial Intelligence; Feasibility Studies; Image Enhancement; Image Interpretation, Computer-Assisted; Nonlinear Dynamics; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2007.894288