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| Author(s): |
Dalcimar Casanova
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Física de São Carlos (IFSC/BT) |
| Defense date: | 2013-07-01 |
| Examining board members: |
Odemir Martinez Bruno;
Adriano Defini Andricopulo;
Milton Groppo Junior;
Zhao Liang;
Luiz Antônio Pereira Neves
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| Advisor: | Odemir Martinez Bruno |
| Abstract | |
Complex networks is a relatively recent field of study, that has called the attention of the scientific community and has been successfully applied in different areas such as computer networking, sociology, medicine, physics, mathematics and others. However the literature shows that there are few works that employ complex networks in feature extraction of images for later analysis or classification. Given an image, it can be modeled as a network, extract topological features and, using these measures, build the classifier desired. This work aims, therefore, investigate this type of application, analyzing new forms of modeling an image as a complex network and investigate some topological features to characterize images. In order to analyze the potential of the techniques developed, we selected a major challenge in the field of computer vision: plant identification by leaf analysis. The plant identification is an important task in many research fields such as biodiversity, ecology, botany, pharmacology and others. (AU) | |
| FAPESP's process: | 08/57313-2 - Complex networks in computer vision, with applications in bioinformatics |
| Grantee: | Dalcimar Casanova |
| Support Opportunities: | Scholarships in Brazil - Doctorate |