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An FPGA‐based smart camera for accurate chlorophyll estimations
Author(s) -
PérezPatricio Madaín,
AguilarGonzález Abiel,
CamasAnzueto Jorge L,
Morales Navarro Nestor Antonio,
GrajalesCoutiño Rubén
Publication year - 2018
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.2489
Subject(s) - transmittance , computer science , field programmable gate array , base (topology) , remote sensing , artificial intelligence , computer vision , mathematics , materials science , computer hardware , optoelectronics , geography , mathematical analysis
Summary In this work, a new chlorophyll estimation approach based on the reflectance/transmittance from the leaf being analyzed is proposed. First, top/underside images from the leaf under analysis are captured, then, the base parameters (reflectance/transmittance) are extracted. Finally, a double‐variable linear regression model estimates the chlorophyll content. To estimate the base parameters, a novel optical arrangement is presented. On the other hand, in order to provide a portable device suitable for chlorophyll estimation under large scale food crops, we have implemented our optical arrangement and our algorithmic formulation inside an field‐programmable gate array (FPGA)‐based smart camera fabric. Experimental results demonstrated that the proposed approach outperforms (in terms of accuracy and processing speed) most previous vision‐based approaches, reaching more than 97% accuracy and delivering fast chlorophyll estimations (near 5 ms per estimation).