Cellulose Materials Identification: The Effect of Dimensionality of Colour Photography Data

Abstract

This paper describes a simple rapid staining microcolorimetric method for analytical fibre material identification using colour vectors of stained fibre material photography. The number of morphological characteristics (nM), number of stains (nS), colour information dimensionality (nDC), and picture elementary points number (npx) can play a key role in distinguishing fibre materials, correct identification, discriminatory power dP (%), and efficacy. Experiments were performed to achieve the most accurate results with a minimum volume of data; the dimensionality reduction was made experimentally by setting nM = 0, nS = 1, nDC , and the effect of number of pixels on the dP (%) was measured. The correct identification was achieved by less than 100 pixels when using 2 colour vectors, and by less than 50 pixels when using 3 colour vectors: R, G, and B. The real area of the pixels used for correct identification was less than 0.1 mm2 in the used model system of the cellulose fibre materials.

Keywords

• Lignocellulosic
• Fibre material identification
• Materials analysis
• Staining
• Scanning
• RGB
• Colorimetry
• Discriminatory analysis
• Dimensionality reduction
• Optical microscopy