IEEE Transactions on Pattern Analysis and Machine Intelligence
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
New methods for matching 3-D objects with single perspective views
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Sense for Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust regression and outlier detection
Robust regression and outlier detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of Quantization Error in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Nonparametric Method for Fitting a Straight Line to a Noisy Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simulation of simplicity: a technique to cope with degenerate cases in geometric algorithms
ACM Transactions on Graphics (TOG)
Determining straight line correspondences from intensity images
Pattern Recognition
International Journal of Computer Vision
A generic integrated line detection algorithm and its object-process specification
Computer Vision and Image Understanding - Special issue on document image understanding and retrieval
International Journal of Computer Vision
Straight-line-based primitive extraction in grey-scale object recognition
Pattern Recognition Letters
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Machine Vision and Applications
Face Recognition Using Line Edge Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A practical approximation algorithm for the LMS line estimator
Computational Statistics & Data Analysis
On Straight Line Segment Detection
Journal of Mathematical Imaging and Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
LSD: A Fast Line Segment Detector with a False Detection Control
IEEE Transactions on Pattern Analysis and Machine Intelligence
Advanced Radon transform using generalized interpolated Fourier method for straight line detection
Computer Vision and Image Understanding
Faster least squares approximation
Numerische Mathematik
Image retrieval based on micro-structure descriptor
Pattern Recognition
Robust line detection using two-orthogonal direction image scanning
Computer Vision and Image Understanding
EDLines: A real-time line segment detector with a false detection control
Pattern Recognition Letters
Locating Structures in Aerial Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
The constrained total least squares technique and its applicationsto harmonic superresolution
IEEE Transactions on Signal Processing
On the equivalence of constrained total least squares andstructured total least squares
IEEE Transactions on Signal Processing
Formulation and solution of structured total least norm problemsfor parameter estimation
IEEE Transactions on Signal Processing
Fast communication: Analysis and improvement of SUSAN algorithm
Signal Processing
IEEE Transactions on Consumer Electronics
Unsupervized Video Segmentation With Low Depth of Field
IEEE Transactions on Circuits and Systems for Video Technology
Learning to Extract Focused Objects From Low DOF Images
IEEE Transactions on Circuits and Systems for Video Technology
On Detection of Multiple Object Instances Using Hough Transforms
IEEE Transactions on Pattern Analysis and Machine Intelligence
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For characterizing straight lines in defocused images, a rectilinear Gaussian model (RGM) is proposed. Based on this model, a novel method for estimating the parameters of straight lines is presented. This method, called gray-scale least square (GLS) method, directly deals with gray-scale image data without requiring any preprocessing and hence no additional noise is introduced. Furthermore, the method is able to simultaneously estimate four parameters of straight lines by performing the algorithm only once, while two parameters can be typically estimated by traditional method. Besides this, all parameters are given in closed-form solution. In order to illustrate the effectiveness of RGM and the GLS method, the experiments are performed on a set of artificial images and natural images. The experimental results show that the GLS method outperforms the traditional method from the point of view of sensitivity to noise and accuracy of parameter estimation.