The extraction of curvilinear structures is an important low-level operation in computer vision
that has many applications. Most existing operators use a simple model for the line that is to …

This paper presents an approach to extract curvilinear structures (lines) and their widths
from two-dimensional images with high accuracy. Models for asymmetric parabolic and …

Novel approaches to extract curvilinear structures, ie, lines and edges, from 2D images are
proposed. For lines, explicit geometric models for line profiles are used to analyze their …

In this paper a method to extract curvilinear structures from digital images is presented. The
approach is based on differential geometric properties of the image function. For each pixel …

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 …

A straight line detection algorithm is presented. The algorithm separates row and column
edges from edge image using their primitive shapes. The edges are labeled, and the …

In this paper, a simple and robust algorithm is proposed for detecting straight line segments
in an edge image. The proposed algorithm is based on small eigenvalue analysis. The …

This paper presents a new approach to the extraction of straight lines in intensity images.
Pixels are grouped into line-support regions of similar gradient orientation, and then the …

The Curvature Scale Space (CSS) technique is considered to be a modern tool in image
processing and computer vision. Direct Curvature Scale Space (DCSS) is defined as the …

In this paper, we present a robust line segment detection algorithm to efficiently detect the
line segments from an input image. Firstly a parameter-free Canny operator, named as …