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Journal ArticleDOI

Two algorithms for constructing a Delaunay triangulation

TLDR
This paper provides a unified discussion of the Delaunay triangulation and two algorithms are presented for constructing the triangulations over a planar set ofN points.
Abstract
This paper provides a unified discussion of the Delaunay triangulation. Its geometric properties are reviewed and several applications are discussed. Two algorithms are presented for constructing the triangulation over a planar set ofN points. The first algorithm uses a divide-and-conquer approach. It runs inO(N logN) time, which is asymptotically optimal. The second algorithm is iterative and requiresO(N 2) time in the worst case. However, its average case performance is comparable to that of the first algorithm.

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Proceedings ArticleDOI

Combining region splitting and edge detection through guided Delaunay image subdivision

TL;DR: Experiments on a real image indicate that the adaptive split-and-merge segmentation method yields good segmentation results even when there is a quadratic sloping of intensities particularly suited for segmenting natural scenes of man-made objects.
Proceedings ArticleDOI

Complete and robust cooperative robot area coverage with limited range

TL;DR: The proposed method starts by locating a set of static guards on the map of the target area and builds a graph called Reduced-CDT, a new environment representation method based on the Constrained Delaunay Triangulation (CDT).
Proceedings ArticleDOI

Augmenting Ridge Curves with Minutiae Triplets for Fingerprint Indexing

TL;DR: The indexing framework based on minutiae triplets is extended by utilizing ridge curve parameters in conjunction withminutiae information to enhance indexing performance and is demonstrated that the proposed technique facilitates the indexing of fingerprint images acquired using different sensors.
Proceedings ArticleDOI

Towards Robust Evaluation of Face Morphing Detection

TL;DR: This work creates face morphing databases with varying characteristics and shows how for a LBP/SVM based morphing detection method that performs on par with the state of the art, the performance collapses with an EER as high as if it is tested across databases with different characteristics.

Lecture Notes on

TL;DR: Every context-free language most problems you've encountered in CS (BFS, DFS, sorting, etc.) and the greatest common divisor of x and y are taught.
References
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Book

Computational geometry

Proceedings ArticleDOI

Closest-point problems

TL;DR: The purpose of this paper is to introduce a single geometric structure, called the Voronoi diagram, which can be constructed rapidly and contains all of the relevant proximity information in only linear space, and is used to obtain O(N log N) algorithms for most of the problems considered.