Classificação de Imagens Utilizando Fusão de Sensores Termal e Visível
DOI:
https://doi.org/10.55972/spectrum.v24i1.396Palavras-chave:
Sensoriamento remoto, Infravermelho, Reconhecimento de padrõesResumo
Utilizando uma câmera com sensor duplo (visível e termal), este trabalho avalia a alteração na exatidão global de quatro classes de interesse utilizando-se diferentes composições de canais nas imagens analisadas. São testadas as composições RGB e RGBI (composição RGB mais canal infravermelho). Os resultados são comparados utilizando os algoritmos k vizinhos mais próximos (k-NN) e máquina de vetores de suporte (SVM). Os resultados experimentais indicam que o uso da composição RGBI aumenta a acurácia na classificação em 9,7%, no k-NN, e 1,9% no SVM.
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