Using a reference color plate to calibrate soil color measured with smartphone cameras

Soil color has long been used as an indicator for soil properties such as soil organic carbon and soil moisture. Recent developments of citizen science have seen increased use of smartphone cameras for soil color measurement. However, there are high errors associated with this technique, especially when used in the field. A major source of the errors is that the color in the smartphone images for a given object is strongly affected by the type of smartphone used and the environmental lighting conditions. To reduce this error, we propose to calibrate the color in a smartphone image by including reference color objects in the picture while taking the photo. To examine the validity of this calibration method, we used a commercially available color plate with 24 color squares covering a wide range in the color space as the reference color objects. The color plate was placed together with 7 Munsell soil color sheets covering the range of soil colors observed in Canada. Pictures were taken with four different smartphones under six lighting conditions. Each color square in the color plate and each color chip in the Munsell soil color sheets were measured with a FieldSpec4 SpectroRadiometer. The FieldSpec4 measurements were converted to RGB values in the RGB color space and Hue, Value, and Chroma in the Munsell color space. These values were considered as reference values (true values). Meanwhile, for each color square in the color plate and each color chip in the Munsell soil color book, the RGB values in each smartphone image were extracted. They were converted to Hue, Value, and Chroma in the Munsell color space as well. These values derived directly from the smartphone images were considered the raw values for the smartphone images. For each smartphone image and for each color parameter, a linear regression was established between the raw and reference values of the color squares on the color plate. For other objects in the same picture, the calibration was conducted by applying the regression equation to adjust the raw values to the calibrated values. The validity of the calibration method was examined by comparing the calibrated values to the FeildSpec4 measured reference values. The results show that the raw values had significant bias for some smartphones and under some lighting conditions. After calibration, the bias has been reduced for most color parameters. In particular, the variations associated with different smartphones and different lighting conditions have been reduced. With the Munsell soil color sheets, the calibrated Hue, Value matched well with the values indicated on the sheets, a substantial improvement from the raw values. However, the calibration did not seem to work well with Chroma and there was no improvement after the calibration process for Chroma.