文献类型：期刊文献

英文题名：Cost-effective wireless system for image-based microalgae biomass estimation with adaptive background correction

作者：Xiao, Hua[1]; Zhang, Qiaoyang[2]; Chen, Haiyun[1]; Hao, Junjie[3]; Tang, Haodong[3]; Wang, Kai[4]; Sun, Xiao Wei[4]

机构：[1] School of Electronic and Information Engineering, Guangdong Ocean University, Zhanjiang, 524088, China; [2] School of Mathematics and Computer Science, Guangdong Ocean University, Zhanjiang, 524088, China; [3] College of Integrated Circuits and Optoelectronic Chips, Shenzhen Technology University, Shenzhen, 518118, China; [4] Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, 518055, China

年份：2026

卷号：459

外文期刊名：Bioresource Technology

收录：EI(收录号：20262620996974)、Scopus(收录号：2-s2.0-105042785759)

语种：英文

外文关键词：Biomass - Cost estimating - Data mining - Microalgae - Polynomial regression - Polynomials

外文摘要：Accurate microalgae biomass estimation is essential for image-based cultivation monitoring, yet conventional RGB-based approaches remain sensitive to background chromaticity variations under different imaging conditions. Here, an adaptive background-corrected framework for image-based microalgae biomass estimation is proposed based on polynomial RGB regression analysis. By preserving directional information within multi-dimensional color vectors, the proposed method improves RGB-based biomass estimation consistency under varying background conditions. The framework is implemented using a low-cost wireless sensing system ( ? 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.