Autor(es)

Bragantini, Jordao ; Martins, Samuel Botter ; Castelo-Fernandez, Cesar ; Falcao, Alexandre Xavier

• Tipo de documento: Artigo Científico
• Fonte: PROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2018; v. 11401, p. 9-pg., 2019-01-01.

Resumo

Image segmentation methods have been actively investigated, being the graph-based approaches among the most popular for object delineation from seed nodes. In this context, one can design segmentation methods by distinct choices of the image graph and connectivity function-i.e., a function that measures how strongly connected are seed and node through a given path. The framework is known as Image Foresting Transform (IFT) and it can define by seed competition each object as one optimum-path forest rooted in its internal seeds. In this work, we extend the general IFT algorithm to extract object information as the trees evolve from the seed set and use that information to estimate arc weights, positively affecting the connectivity function, during segmentation. The new framework is named Dynamic IFT (DynIFT) and it can make object delineation more effective by exploiting color, texture, and shape information from those dynamic trees. In comparison with other graph-based approaches from the state-of-the-art, the experimental results on natural images show that DynIFT-based object delineation methods can be significantly more accurate. (AU)

• Processo FAPESP: 18/08951-8 - PyIFT: processamento de imagem usando a transformada imagem-floresta em Python
• Beneficiário: Jordão Okuma Barbosa Ferraz Bragantini
• Modalidade de apoio: Bolsas no Brasil - Iniciação Científica
• Processo FAPESP: 14/12236-1 - AnImaLS: Anotação de Imagem em Larga Escala: o que máquinas e especialistas podem aprender interagindo?
• Beneficiário: Alexandre Xavier Falcão
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 17/03940-5 - Aprendizado Interativo de Dicionários Visuais Aplicado à Classificação de Imagens
• Beneficiário: César Christian Castelo Fernández
• Modalidade de apoio: Bolsas no Brasil - Doutorado