Curvature Based Corner Detector for Discrete, Noisy and Multi-Scale Contours

  title={Curvature Based Corner Detector for Discrete, Noisy and Multi-Scale Contours},
  author={Bertrand Kerautret and Jacques-Olivier Lachaud and Beno{\^i}t Naegel},
  journal={Int. J. Shape Model.},
Estimating curvature on digital shapes is known to be a difficult problem even in high resolution images 10,19. Moreover the presence of noise contributes to the instability of the estimators and limits their use in many computer vision applications like corner detection. Several recent curvature estimators 16,13,15, which come from the discrete geometry community, can now process damaged data and integrate the amount of noise in their analysis. In this paper, we propose a comparative… 
Multigrid-convergence of digital curvature estimators
Three digital curvature estimators that aim at this objective are reviewed: a first one based on maximal digital circular arc, a second one using a global optimization procedure, and a third one that is a digital counterpart to integral invariants and that works on 2D and 3D shapes.
Robust reconstructions by multi-scale/irregular tangential covering
This work explains its novel complete pipeline, and presents its experimental evaluation by considering both synthetic and real image data, and shows that this is a robust approach, with respect to selected references from state-of-the-art, and by considering a multi-scale noise evaluation process.
Circular Arc Reconstruction of Digital Contours with Chosen Hausdorff Error
This work proposes to reconstruct the shape with circular arcs by exploiting the recent curvature estimators to approximate a digital shape with as few arcs as possible at a given scale, specified by a maximal admissible Hausdorff distance.
Geometric Total Variation for Image Vectorization, Zooming and Pixel Art Depixelizing
An original method for vectorizing an image or zooming it at an arbitrary scale that relies on the resolution of a geometric variational model and therefore offers theoretic guarantees and is particularly appealing for processing images with low quantization like pixel art.
Accelerating the computation of multi-scale visual curvature for simplifying a large set of polylines with Hadoop
The proposed accelerated MVC algorithm has great potential in many GIScience applications, including map generalization, DEM simplification, and spatial-temporal data compression.
Courbure discrète : théorie et applications
These are the notes of my talk presented in the colloquium on discrete curvature at the CIRM, in Luminy (France) on November 21st, 2013, in which we study the space of triangulations from a purely
Radar target recognition using time-frequency analysis and polar transformation
  • J. Cexus, A. Toumi
  • Computer Science, Mathematics
    2018 4th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)
  • 2018
A new method for Automatic Radar Targets Recognition is presented based on Inverse Synthetic Aperture Radar using k-Nearest Neighbors, Fuzzy k-NN, Neural network and Bayesian classifiers to achieve recognition of radar target recognition tasks.
Discrete curvature: theory and applications
The present volume contains the proceedings of the 2013 Meeting on discrete curvature, held at CIRM, Luminy, France, with a focus on both theory and applications.


Comparison of Discrete Curvature Estimators and Application to Corner Detection
This paper compares and analyse the performances of these curvature estimators on several types of contours and measures execution time on both perfect and noisy shapes.
Corner Detection Based on Morphological Disk Element
A new morphological detector, which uses simple symmetric disk element in corner detection to avoid element rotation and improve the running efficiency and the ability in estimating corner angle and orientation during the detection.
Error-Bounds on Curvature Estimation
One interesting result is that, contrary to intuition, the accurate calculation of the curvature for low-curvature regions is in fact impossible for common image-sizes, while reasonable results may under favourable conditions be obtained for higher-curVature regions.
A Unified Curvature Definition for Regular, Polygonal, and Digital Planar Curves
The proposed definition of visual curvature is the first ever that applies to regular curves as defined in differential geometry as well as to turn angles of polygonal curves and it yields stable curvature estimates of curves in digital images even under sever distortions.
Robust Estimation of Curvature along Digital Contours with Global Optimization
A new curvature estimator based on global optimisation is introduced that exploits the geometric properties of digital contours by using local bounds on tangent directions defined by the maximal digital straight segments.
Curvature Estimation in Noisy Curves
An algorithm of estimation of the curvature at each point of a general discrete curve in O(n log2 n) is proposed. It uses the notion of blurred segment, extending the definition of segment of
Optimal Time Computation of the Tangent of a Discrete Curve: Application to the Curvature
Vialard has proposed a O(l) algorithm for computing the tangent in one point of a discrete curve where l is the average length of the tangents, and the resulting algorithm has a O (n) complexity and is thus optimal.
An improved corner detection algorithm based on chain-coded plane curves
Binomial Convolutions and Derivatives Estimation from Noisy Discretizations
A new method to estimate derivatives of digitized functions is presented, which is convergent and can be computed by using only the arithmetic operations, and a new notion which solves the problem of correspondence between the parametrization of a continuous curve and the pixels numbering of a discrete object is introduced.