Online recognition of sketched arrow-connected diagrams

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F16%3A00301690" target="_blank" >RIV/68407700:21730/16:00301690 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/16:00301690

Výsledek na webu

<a href="http://link.springer.com/article/10.1007/s10032-016-0269-z" target="_blank" >http://link.springer.com/article/10.1007/s10032-016-0269-z</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10032-016-0269-z" target="_blank" >10.1007/s10032-016-0269-z</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Online recognition of sketched arrow-connected diagrams

Popis výsledku v původním jazyce

We introduce a new, online, stroke-based recognition system for hand-drawn diagrams which belong to a group of documents with an explicit structure obvious to humans but only loosely defined from the machine point of view. We propose a model for recognition by selection of symbol candidates, based on evaluation of relations between candidates using a set of predicates. It is suitable for simpler structures where the relations are explicitly given by symbols, arrows in the case of diagrams. Knowledge of a specific diagram domain is used—the two domains are flowcharts and finite automata. Although the individual pipeline steps are tailored for these, the system can readily be adapted for other domains. Our entire diagram recognition pipeline is outlined. Its core parts are text/non-text separation, symbol segmentation, their classification and structural analysis. Individual parts have been published by the authors previously and so are described briefly and referenced. Thorough evaluation on benchmark databases shows the accuracy of the system reaches the state of the art and is ready for practical use. The paper brings several contributions: (a) the entire system and its state-of-the-art performance; (b) the methodology exploring document structure when it is loosely defined; (c) the thorough experimental evaluation; (d) the new annotated database for online sketched flowcharts and finite automata diagrams.

Název v anglickém jazyce

Online recognition of sketched arrow-connected diagrams

Popis výsledku anglicky

We introduce a new, online, stroke-based recognition system for hand-drawn diagrams which belong to a group of documents with an explicit structure obvious to humans but only loosely defined from the machine point of view. We propose a model for recognition by selection of symbol candidates, based on evaluation of relations between candidates using a set of predicates. It is suitable for simpler structures where the relations are explicitly given by symbols, arrows in the case of diagrams. Knowledge of a specific diagram domain is used—the two domains are flowcharts and finite automata. Although the individual pipeline steps are tailored for these, the system can readily be adapted for other domains. Our entire diagram recognition pipeline is outlined. Its core parts are text/non-text separation, symbol segmentation, their classification and structural analysis. Individual parts have been published by the authors previously and so are described briefly and referenced. Thorough evaluation on benchmark databases shows the accuracy of the system reaches the state of the art and is ready for practical use. The paper brings several contributions: (a) the entire system and its state-of-the-art performance; (b) the methodology exploring document structure when it is loosely defined; (c) the thorough experimental evaluation; (d) the new annotated database for online sketched flowcharts and finite automata diagrams.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

<a href="/cs/project/GA15-04960S" target="_blank" >GA15-04960S: SeLeCt - struktury, učení a kognice</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal on Document Analysis and Recognition

ISSN

1433-2833

e-ISSN

—

Svazek periodika

19

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

15

Strana od-do

253-267

Kód UT WoS článku

000382088800005

EID výsledku v databázi Scopus

2-s2.0-84974851308