A Camera-Based Structural Color Sensor Using Image Processing Algorithm with RGB to Hue Transformation

A structural color-based sensor (e.g., for measuring strain, humidity, or force), which is wireless and capable of providing visual (rather than electrical) measurements, is very attractive during the current development of the Internet of Things (IoT). Despite their advantages, such sensors currently require spectrometry-based measurements, which has led to limited use because of additional installation and measurement costs. Here, a camera-based sensing method is introduced for structural color-based sensors that involves simple image processing, in which RGB data are converted to hue data. The RGB data change with the incident light intensity and certainly affect the hue values from the RGB conversion. But, this would be limited to hue data if the system is with stabilized illumination. The procedure is experimentally verified using a structural color-based strain sensor as a case study. Micro- and mesoscale sensors are fabricated to demonstrate the proposed method, including multi-sensor detection; determine the degree of hysteresis, sensitivity, and real-time measurement capability; and validate its performance using two different cameras. Because of its simple methodology and low cost, this method is expected to reduce barriers to the application of structural color sensors; it may significantly accelerate the adoption of the IoT paradigm within various engineering fields.

Automated summary

This article introduces a camera-based sensing method for structural color sensors, which involves simple image processing to convert RGB data into hue data. Through experimental verification, this method has been proven effective and cost-efficient in application, potentially accelerating the adoption of the Internet of Things in various engineering fields.