Randomized neural network based signature for color texture classification

Autor(es)

Mesquita Sa Junior, Jarbas Joacide ^{[1, 2]} ; Backes, Andre Ricardo ^[3] ; Bruno, Odemir Martinez ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Sao Carlos Inst Phys, POB 369, BR-13560970 Sao Carlos, SP - Brazil

^[2] Univ Fed Ceara, Dept Comp Engn, Campus Sobral, Rua Coronel Estanislau Frota 563, BR-62010560 Sobral, CE - Brazil

^[3] Univ Fed Uberlandia, Sch Comp Sci, Ave Joao Naves Avila 2121, BR-38408100 Uberlandia, MG - Brazil

• Tipo de documento: Artigo Científico
• Fonte: MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING; v. 30, n. 3, p. 1171-1186, JUL 2019.
• Citações Web of Science: 0

Resumo

Color texture analysis is an important subject in computer vision research. This paper presents an innovative and powerful color texture analysis method based on a randomized neural network. This approach uses the weights of the neural network as attributes for a color feature vector. Experiments were performed in three well-established benchmarks (Vistex, USPtex and Outex) and two rotated versions of these datasets (Vistex and Outex). The results were promising, surpassing the accuracies of most of the compared methods. This achievement allows us to affirm that the proposed approach is a valuable tool to be included in color texture analysis field. (AU)

• Processo FAPESP: 16/18809-9 - Deep learning e redes complexas aplicados em visão computacional
• Beneficiário: Odemir Martinez Bruno
• Linha de fomento: Auxílio à Pesquisa - Parceria para Inovação Tecnológica - PITE
• Processo FAPESP: 14/08026-1 - Visão artificial e reconhecimento de padrões aplicados em plasticidade vegetal
• Beneficiário: Odemir Martinez Bruno
• Linha de fomento: Auxílio à Pesquisa - Regular