DocumentCode :
3487376
Title :
Sketch recognition using particle swarm algorithms
Author :
Meseery, Maha El ; Din, Mahmoud Fakhr El ; Mashali, Samia ; Fayek, Magda ; Darwish, Nevin
Author_Institution :
Signals Process. Group, Electron. Res. Inst., Cairo, Egypt
fYear :
2009
fDate :
7-10 Nov. 2009
Firstpage :
2017
Lastpage :
2020
Abstract :
Sketch recognition is defined as the process of identifying symbols that users draw using single or multiple strokes. Users draw strokes using a pen and the system immediately interprets their strokes as objects that can be easily manipulated. This paper uses Particle Swarm Optimization Algorithm (PSO) to divide the strokes the user draws into meaningful geometric primitives. These geometric primitives are grouped to formulate symbols which are further identified. The results show that using PSO improves segmentation results which guide the symbol recognition phase. This paper uses Support Vector Machines (SVM) classifier which further improves the final recognition accuracy.
Keywords :
image recognition; image segmentation; particle swarm optimisation; support vector machines; PSO; geometric primitives; identifying symbol process; multiple strokes; particle swarm optimization algorithm; single strokes; sketch recognition; support vector machines; Design engineering; Hybrid power systems; Particle swarm optimization; Power engineering and energy; Power engineering computing; Shape; Signal processing algorithms; Support vector machine classification; Support vector machines; Writing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
ISSN :
1522-4880
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2009.5414040
Filename :
5414040
Link To Document :
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