Spectral methods in image segmentation: a combined approach

• Autor(es): Monteiro, Fernando C. ; Campilho, Aurélio
• Data: 2005
• Identificador Persistente: http://hdl.handle.net/10198/1836
• Origem: Biblioteca Digital do IPB
• Assunto(s): Image segmentation; Spectral methods; Normalized cuts
• Tipo de Documento: Parte ou capítulo de livro
• Idioma: Inglês

Descrição

Indexado ISI Grouping and segmentation of images remains a challenging problem in computer vision. Recently, a number of authors have demonstrated a good performance on this task using spectral methods that are based on the eigensolution of a similarity matrix. In this paper, we implement a variation of the existing methods that combines aspects from several of the best-known eigenvector segmentation algorithms to produce a discrete optimal solution of the relaxed continuous eigensolution.