Software Development for Colourimetric and Spectral Data Processing: Pycolourimetry

Abstract

Abstract:Archaeological documentation is a complex process where the technical measurement and specification of colour is a key aspect. In the last years heritage documentation processes have largely benefited from the application of digital recording methods, imagery analysis software and technologies that offers great advantages over the traditional methods. The rigorous processing of colourimetric data requires software packages with specific colourimetric technical characteristics. In this paper we report on our in-house pyColourimetry software that was developed and tested taking into account the recommendations of the Commission Internationale de l'Éclairage (CIE). The objective is to apply a rigorous procedure for the characterisation of cameras based a priori on polynomial models. Most of the digital cameras capture colour information in the well-known RGB format, but the signals generated by the digital camera are device dependent. By means of the characterisation we establish the relationship between device dependent RGB values and the tristimulus coordinates defined by the CIE standard colourimetric observer. Once the camera is characterised, users have the potential to obtain output images in the sRGB space that is independent of the sensor of the camera. pyColourimetry software allows users to control the entire digital image processing and the colourimetric data workflow proposed. We applied the methodology on a set of pictures targeting Levantine rock art motifs in Cova dels Cavalls (Castellón, Spain) which is considered part of a UNESCO World Heritage Site. The outcomes obtained are satisfactory and very promising for proper colour documentation in cultural heritage estudies. Key words: Camera characterisation, Rock Art, Colourimetry, CIE Colour spaces, Python Resumen:La documentación del patrimonio arqueológico es un proceso complejo donde la correcta medición del color es un aspecto clave. En los últimos años los procesos de documentación se han beneficiado gracias al uso de imágenes digitales, software de tratamiento de imágenes, así como de otras tecnologías frente a los métodos tradicionales. El procesamiento riguroso de datos colorimétricos requiere paquetes de software con características técnicas específicas. En este artículo presentamos un informe sobre el software pyColourimetry, desarrollado y testado teniendo en cuenta las recomendaciones de la Comisión Internacional de la Iluminación (CIE). Mediante este software el susuario puede caracterizar cámaras digitales a partir de modelos polinomiales. La mayoría de cámaras digitales captan información del color en el conocido sistema RGB. Sin embargo, la señal generada depende del dispositivo. A partir de la caracterización establecemos la relación entre los valores RGB dependientes y las coordenadas independientes CIE triestímulo. Una vez caracterizada la cámara se obtienen imágenes en el espacio sRGB, independiente del sensor empleado. El software pyColourimetry permite a los usuarios controlar todo el procesamiento digital de imágenes y ...

Camera Characterisation Based on Skin-Tone Colours for Rock Art Recording

“…Camera characterisation is a suitable methodology for cultural heritage documentation techniques. For a detailed description of the methodology, formulation and software we further recommend the reader to examine our previous articles published about the camera characterisation procedure [10,11].…”

“…All computations, including colourimetric and image processing, were done with our own software, named pyColourimetry, which was developed for previous colour experiments [11].…”

A Gaussian Process Model for Color Camera Characterization: Assessment in Outdoor Levantine Rock Art Scenes

“…This software was written in the Python programming language following the CIE recommendations. It allows raw RGB data extraction from conventional camera formats and implements other colorimetric functions such as transformation among color spaces, color difference calculation, or spectral data treatment [34].…”

Dominant Color Extraction with K-Means for Camera Characterization in Cultural Heritage Documentation

“…Although this color chart has 140 patches, we used only the 96 chromatic central chips (and 15 grey scale central ones) without considering the external patches on the edges. The RAW RGB data for these patches were extracted from the images using our own software named pyColourimetry [39].…”