| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 9.25 MB | Adobe PDF |
Orientador(es)
Resumo(s)
Precision agriculture is gaining an increasing interest in the current farming paradigm. This new production concept relies on the
use of information technology (IT) to provide a control and supervising structure that can lead to better management policies. In
this framework, imaging techniques that provide visual information over the farming area play an important role in production
status monitoring. As such, accurate representation of the gathered production images is amajor concern, especially if those images
are used in detection and classification tasks.Real scenes, observed in natural environment, present high dynamic ranges that cannot
be represented by the common LDR (Low Dynamic Range) devices. However, this issue can be handled by High Dynamic Range
(HDR) images since they have the ability to store luminance information similarly to the human visual system. In order to prove
their advantage in image processing, a comparative analysis between LDR and HDR images, for fruits detection and counting, was
carried out.The obtained results show that the use of HDR images improves the detection performance to more than 30% when
compared to LDR.
Descrição
Palavras-chave
High-dynamic-range Tone reproduction System Scenes Yield Localization Display
Contexto Educativo
Citação
Pinho, Tatiana M.; Coelho, J.P.; Oliveira, Josenalde; Boaventura-Cunha, José (2017). Comparative analysis between LDR and HDR images for automatic fruit recognition and counting. Journal of Sensors. ISSN 1687-725X. p. 1-12