Abstract: To enable rapid and convenient detection of zearalenone (ZEN) and aflatoxins (AFB1) in coarse cereals, this work developed an aptamer-based sensor integrated with image analysis software. The sensor utilizes specific aptamers targeting ZEN and AFB1 as recognition elements, gold nanoparticles (AuNPs) as the colorimetric indicator, and NaCl as the chromogenic agent. Images of samples captured by a smartphone were analyzed using ImageJ software through measuring the integrated pixel density, allowing for specific and rapid detection of ZEN and AFB1 in ten different types of coarse cereals. Under optimal conditions, the aptasensor based on microplate reader absorbance measurement showed linear detection ranges of 0.05–3 ng/g for ZEN and 0.2–8 ng/g for AFB1, with calibration equations y=0.021x+0.3353 (R²=0.9983) and y=0.0207x+0.3075 (R²=0.9986), and detection limits of 0.035 ng/g and 0.1 ng/g, respectively. When using smartphone image acquisition combined with ImageJ analysis as an alternative method, secondary calibration equations were derived: y=−16.141x+189.88 (R²=0.991) for ZEN and y=−12.928x+247.08 (R²=0.9901) for AFB1, with LODs of 0.037 ng/g and 0.106 ng/g. Method validation confirmed good accuracy and precision, with spike recoveries ranging from 85.88~101.13% (RSD 1.56~5.34%) for ZEN and 87.76~109.30% (RSD 0.9~5.07%) for AFB1. The aptasensor successfully detected ZEN and AFB1 in all ten tested coarse cereal samples. By integrating smartphone image analysis, this approach achieves highly sensitive, rapid (15 min) and accurate detection of both mycotoxins in coarse cereals, making it an effective tool for on-site screening applications.