Automatic Label Placement for Technical Drawings

A lot of research has been done to automatically label geographical maps. In the field of study, other types of images, like technical drawings, are almost completely disregarded. In enormous industrial projects, like shipbuilding or designing process plant facilities, there are countless of drawings produced. Labeling these drawings needs to be done manually by the designers and automating the labeling of these drawings would save countless of hours of the designers time. This thesis aims to develop a method to conduct automatic labeling in the context of technical drawings. The main target are drawings produced in process plant design and marine industry, but the final solution is general enough to be used for other types of technical drawings as well. To achieve this, a set of requirements for the task is collected and an implementation principle for automatic labeling of technical drawings is presented. The solution is based on prior research done regarding automatic labeling of geographical maps as well as a new label candidate generation heuristic. The developed solution is evaluated by conducting an empirical study on an implementation of the new principle. The empirical study indicates that the solution is practical enough to be used in real environments. However, it also reveals some improvements needed in the quality of the labeling as well as its performance.Maantieteellisten karttojen automaattinen labelointi on laajalti tutkittu aihe. Tutkimusalalla muun tyyppiset kuvat, kuten tekniset piirustukset, eivät ole juuri saaneet huomiota. Suurissa teollisissa projekteissa, kuten laivojen tai prosessiteollisuuslaitosten suunnittelussa, tuotetaan suuria määriä piirustuksia. Projekteissa suunnittelijat joutuvat itse labeloimaan kyseiset piirustukset, mikä vie merkittävästi aikaa. Näiden piirustusten automaattinen labelointi säästäisi lukemattomia työtunteja suunnittelijoilta. Tämä diplomityö pyrkii kehittämään automaattisen labelointimenetelmän teknisille piirustuksille. Päätavoite on laivanrakennuksessa ja prosessiteollisuuslaitosten suunnittelussa tuotettujen piirustusten labeloinnin automatisointi. Kehitetty menetelmä on kuitenkin yleiskäyttöinen myös muunkaltaisissa piirustuksissa. Työssä ensin kartoitetaan teknisten piirustusten automaattisen labeloinnin vaatimukset, minkä jälkeen kehitetään ko. vaatimukset täyttävä menetelmä. Menetelmä perustuu tutkimustietoon karttojen automaattisesta labeloinnista sekä tässä työssä kehitettyyn uuteen labeleiden kandidaattien generointi -heuristiikkaan. Kehitetty menetelmä arvioidaan empiirisellä tutkimuksella. Empiirinen tutkimus osoittaa, että kehitetty menetelmä on riittävän käyttökelpoinen todellisessa ympäristössä. Menetelmässä ilmeni kuitenkin vielä parannettavaa labeloinnin laadussa sekä menetelmän suoritusnopeudessa

Multi-Sided Boundary Labeling

In the Boundary Labeling problem, we are given a set of $n$ points, referred to as sites, inside an axis-parallel rectangle $R$, and a set of $n$ pairwise disjoint rectangular labels that are attached to $R$ from the outside. The task is to connect the sites to the labels by non-intersecting rectilinear paths, so-called leaders, with at most one bend. In this paper, we study the Multi-Sided Boundary Labeling problem, with labels lying on at least two sides of the enclosing rectangle. We present a polynomial-time algorithm that computes a crossing-free leader layout if one exists. So far, such an algorithm has only been known for the cases in which labels lie on one side or on two opposite sides of $R$ (here a crossing-free solution always exists). The case where labels may lie on adjacent sides is more difficult. We present efficient algorithms for testing the existence of a crossing-free leader layout that labels all sites and also for maximizing the number of labeled sites in a crossing-free leader layout. For two-sided boundary labeling with adjacent sides, we further show how to minimize the total leader length in a crossing-free layout

Boundary Labeling for Rectangular Diagrams

Given a set of n points (sites) inside a rectangle R and n points (label locations or ports) on its boundary, a boundary labeling problem seeks ways of connecting every site to a distinct port while achieving different labeling aesthetics. We examine the scenario when the connecting lines (leaders) are drawn as axis-aligned polylines with few bends, every leader lies strictly inside R, no two leaders cross, and the sum of the lengths of all the leaders is minimized. In a k-sided boundary labeling problem, where 1 <= k <= 4, the label locations are located on the k consecutive sides of R. In this paper we develop an O(n^3 log n)-time algorithm for 2-sided boundary labeling, where the leaders are restricted to have one bend. This improves the previously best known O(n^8 log n)-time algorithm of Kindermann et al. (Algorithmica, 76(1):225-258, 2016). We show the problem is polynomial-time solvable in more general settings such as when the ports are located on more than two sides of R, in the presence of obstacles, and even when the objective is to minimize the total number of bends. Our results improve the previous algorithms on boundary labeling with obstacles, as well as provide the first polynomial-time algorithms for minimizing the total leader length and number of bends for 3- and 4-sided boundary labeling. These results settle a number of open questions on the boundary labeling problems (Wolff, Handbook of Graph Drawing, Chapter 23, Table 23.1, 2014)

Visualizing Geophylogenies - Internal and External Labeling with Phylogenetic Tree Constraints

A geophylogeny is a phylogenetic tree where each leaf (biological taxon) has an associated geographic location (site). To clearly visualize a geophylogeny, the tree is typically represented as a crossing-free drawing next to a map. The correspondence between the taxa and the sites is either shown with matching labels on the map (internal labeling) or with leaders that connect each site to the corresponding leaf of the tree (external labeling). In both cases, a good order of the leaves is paramount for understanding the association between sites and taxa. We define several quality measures for internal labeling and give an efficient algorithm for optimizing them. In contrast, minimizing the number of leader crossings in an external labeling is NP-hard. We show nonetheless that optimal solutions can be found in a matter of seconds on realistic instances using integer linear programming. Finally, we provide several efficient heuristic algorithms and experimentally show them to be near optimal on real-world and synthetic instances