The doctoral research conducted by Jari Isohanni at the University of Vaasa has opened up exciting possibilities for the packaging industry with the development of smart packaging that utilizes color-changing printing inks and machine learning for color recognition. This advancement offers cost-effective solutions for various sectors such as food and beverage, healthcare, logistics, and electronics.
In the past, there has been a lack of research on the most suitable color recognition methods for different scenarios. Isohanni’s research addressed this gap by comparing the effectiveness of machine learning and color difference methodologies in various situations.
“My research revealed that conventional computational methods are effective in recognizing significant color differences. However, for detecting subtle changes and varying conditions, convolutional neural networks based on artificial intelligence proved to be the most efficient,” Isohanni explained.
Choosing the Right Method for the Right Application
The use of functional printing inks that change color based on environmental conditions opens up new avenues for industries compared to traditional electronic sensors. The ability to detect minor color changes can revolutionize quality control processes and offer innovative solutions for industries.
“The subtle and rapid color changes in printing inks are challenging to detect accurately using current machine vision techniques. By the time these changes are noticeable through conventional means, it might be too late or damage may have already occurred,” Isohanni elaborated.
Artificial intelligence enables automatic color recognition in industries with precision comparable to human vision, introducing new possibilities for quality control and other applications. The research findings can lead to the development of consumer-friendly indicators for assessing the condition of products, such as food items, with minimal additional costs compared to electronic smart packaging solutions.
“Expensive electronic sensors are not feasible for simple products like lettuce packaging due to cost implications and recycling challenges. Printed indicators offer a practical and cost-effective alternative,” Isohanni noted.
This research not only presents an environmentally friendly solution but also opens up opportunities for process improvement and enhanced consumer information. The applications of this technology span across various industries, including food, healthcare, logistics, and electronics, for monitoring shelf life, transport conditions, and product damage.
More information:
Dissertation: Recognition of Subtle Color Differences : A Comparative Study of Machine Learning and Color Difference Metrics
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Smart packaging reveals product condition through color changes (2025, August 27)
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