Propagator method for an application to contour estimation
Pattern Recognition Letters
SLIDE: subspace-based line detection
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
Strongly concave star-shaped contour characterization by algebra tools
Signal Processing
Hand posture classification by means of a new contour signature
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
Multi-line fitting using two-stage iterative adaptive approach
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
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A signal processing method is developed for solving the problem of fitting multiple lines in a two-dimensional image. It formulates the multi-line-fitting problem in a special parameter estimation framework such that a signal structure similar to the sensor array processing signal representation is obtained. Then the recently developed algorithms in that formalism can be exploited to produce super-resolution estimates for line parameters. The number of lines may also be estimated in this framework. The signal representation used can be generalized to handle problems of line fitting and of straight edge detection. Details of the proposed algorithm and several experimental results are presented. The method exhibits considerable computational speed superiority over existing single- and multiple-line-fitting algorithms such as the Hough transform method. Potential applications include road tracking in robotic vision, mask wafer alignment in semiconductor manufacturing, aerial image analysis, text alignment in document analysis, and particle tracking in bubble chambers