Image calibration and analysis toolbox – a free software suite for objectively measuring reflectance, colour and pattern. Issue 11 (6th August 2015)

• Record Type: Journal Article
• Authors: Troscianko, Jolyon; Stevens, Martin
• Is Part Of: Methods in ecology and evolution. Volume 6:Issue 11(2015:Nov.)
• Page Start: 1320
• Page End: 1331
• Publication Date: 2015-08-06
• Subjects: animal coloration -- camera calibration -- colour measurement -- colour vision -- communication -- cone‐catch quanta -- image processing -- pattern analysis -- signalling -- spectrometer; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.12439
• Languages: English
• ISSNs: 2041-210X

Abstract

Summary: Quantitative measurements of colour, pattern and morphology are vital to a growing range of disciplines. Digital cameras are readily available and already widely used for making these measurements, having numerous advantages over other techniques, such as spectrometry. However, off‐the‐shelf consumer cameras are designed to produce images for human viewing, meaning that their uncalibrated photographs cannot be used for making reliable, quantitative measurements. Many studies still fail to appreciate this, and of those scientists who are aware of such issues, many are hindered by a lack of usable tools for making objective measurements from photographs. We have developed an image processing toolbox that generates images that are linear with respect to radiance from the RAW files of numerous camera brands and can combine image channels from multispectral cameras, including additional ultraviolet photographs. Images are then normalised using one or more grey standards to control for lighting conditions. This enables objective measures of reflectance and colour using a wide range of consumer cameras. Furthermore, if the camera's spectral sensitivities are known, the software can convert images to correspond to the visual system (cone‐catch values) of a wide range of animals, enabling human and non‐human visual systems to be modelled. The toolbox also provides image analysis tools that can extract luminance (lightness), colour and pattern information. Furthermore, all processing is performed on 32‐bit floating point images rather than commonly used 8‐bit images. This increases precision and reduces the likelihood of data loss through rounding error or saturation of pixels, while also facilitating the measurement of objects with shiny or fluorescent properties. All cameras tested using this software were found to demonstrate a linear response within each image and across a range of exposure times. Cone‐catch mapping functions were highly robust, converting images to several animal visual systems and yielding data that agreed closely with spectrometer‐based estimates. Our imaging toolbox is freely available as an addition to the open source ImageJ software. We believe that it will considerably enhance the appropriate use of digital cameras across multiple areas of biology, in particular researchers aiming to quantify animal and plant visual signals.