Shape based image retrieval and classification

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2010

Autores

João Ferreira de Carvalho Castro Nunes (Autor) FEUP; Pedro Miguel Moreira (Autor) Outra; João Manuel Ribeiro da Silva Tavares (Autor) FEUP

Ata de Conferência Internacional

Título: In Proceeding of the 5ª Conferencia Ibérica de Sistemas y Tecnologías de la Información (CISTI 2010)

Páginas: 433-438

5ª Conferencia Ibérica de Sistemas y Tecnologías de la Información (CISTI 2010)

Santigo de Compostela, 16 al 19 de Junio de 2010

Indexação

ISI Web of Knowledge - 1 Citação

ISI Web of Science

Scopus - 15 Citações

INSPEC

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Outras ciências da engenharia e tecnologias

CORDIS: Ciências Tecnológicas > Tecnologia > Tecnologia de computadores > Processamento de imagem

Outras Informações

ID Authenticus: P-003-CWA

Abstract (EN): Content based retrieval and recognition of objects represented in images is a challenging problem making it an active research topic. Shape analysis is one of the main approaches to the problem. In this paper we propose the use of a reduced set of features to describe 2D shapes in images. The design of the proposed technique aims to result in a short and simple to extract shape description. We conducted several experiments for both retrieval and recognition tasks and the results obtained demonstrate usefulness and competiveness against existing descriptors. For the retrieval experiment the achieved bull¿s eye performance is about 60%. Recognition was tested with three different classifiers: decision trees (DT), k-nearest neighbor (kNN) and support vector machines (SVM). Estimated mean accuracies range from 69% to 86% (using 10-fold cross validation). The SVM classifier presents the best performance, followed by the simple kNN classifier.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6