20,397 research outputs found
Many-to-One Boundary Labeling with Backbones
In this paper we study \emph{many-to-one boundary labeling with backbone
leaders}. In this new many-to-one model, a horizontal backbone reaches out of
each label into the feature-enclosing rectangle. Feature points that need to be
connected to this label are linked via vertical line segments to the backbone.
We present dynamic programming algorithms for label number and total leader
length minimization of crossing-free backbone labelings. When crossings are
allowed, we aim to obtain solutions with the minimum number of crossings. This
can be achieved efficiently in the case of fixed label order, however, in the
case of flexible label order we show that minimizing the number of leader
crossings is NP-hard.Comment: 23 pages, 10 figures, this is the full version of a paper that is
about to appear in GD'1
LevelScheme: A level scheme drawing and scientific figure preparation system for Mathematica
LevelScheme is a scientific figure preparation system for Mathematica. The
main emphasis is upon the construction of level schemes, or level energy
diagrams, as used in nuclear, atomic, molecular, and hadronic physics.
LevelScheme also provides a general infrastructure for the preparation of
publication-quality figures, including support for multipanel and inset
plotting, customizable tick mark generation, and various drawing and labeling
tasks. Coupled with Mathematica's plotting functions and powerful programming
language, LevelScheme provides a flexible system for the creation of figures
combining diagrams, mathematical plots, and data plots.Comment: LaTeX (RevTeX), 10 pages, associated files available from
http://wnsl.physics.yale.edu/levelschem
Mixed Map Labeling
Point feature map labeling is a geometric problem, in which a set of input
points must be labeled with a set of disjoint rectangles (the bounding boxes of
the label texts). Typically, labeling models either use internal labels, which
must touch their feature point, or external (boundary) labels, which are placed
on one of the four sides of the input points' bounding box and which are
connected to their feature points by crossing-free leader lines. In this paper
we study polynomial-time algorithms for maximizing the number of internal
labels in a mixed labeling model that combines internal and external labels.
The model requires that all leaders are parallel to a given orientation , whose value influences the geometric properties and hence the
running times of our algorithms.Comment: Full version for the paper accepted at CIAC 201
Thick 2D Relations for Document Understanding
We use a propositional language of qualitative rectangle relations to detect the reading order from document images. To this end, we define the notion of a document encoding rule and we analyze possible formalisms to express document encoding rules such as LATEX and SGML. Document encoding rules expressed in the propositional language of rectangles are used to build a reading order detector for document images. In order to achieve robustness and avoid brittleness when applying the system to real life document images, the notion of a thick boundary interpretation for a qualitative relation is introduced. The framework is tested on a collection of heterogeneous document images showing recall rates up to 89%
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