Quality inspection is recognized as a critical aspect of manufacturing, profoundly affecting product integrity and customer satisfaction. The paper presents the application of the multimodal imaging technique, specifically infrared (IR) and visible light (VIS) imaging, that is investigated to enhance the inspection of heat-sealed packages. The distinct strengths of each imaging modality are leveraged to address the limitations associated with single-sensor approaches. An effective image fusion algorithm is proposed to integrate complementary information, facilitating the detection of subtle defects in heat-sealed packages, such as inconsistencies in seals and contamination. Experimental results show that the proposed method enhances defect classification and overall inspection accuracy by synthesizing redundant and complementary data sources.