Study on the measurement and evaluation of cotton color using image analysis

Abstract

Color is an important property to grade cotton. However, precise measurement and comprehensive evaluation of cotton color have not yet been carried out because of instrumental defect, colorful trash and less indicators. This work proposed an accurate method of color measurement and cotton grading. In order to remove the influence of trash on result, a novel trash detection method based on color features of defined three categories of trash and cotton was introduced. In order to improve the accuracy of trash detection, a method based on two-step threshold algorithm is proposed. The original images stored in sRGB format was transformed into binary images according to fixed thresholds and ‘Otsu’ algorithm. Compared to previous trash detection methods, the two-steps detection method was more suitable for cottons with different trash-content. Indicators expressed in Hunter color space were determined by the conversion referring to optical theory and light source. The feasibility of the proposed method was confirmed by comparing the present result with that obtained from standard instruments system. Furthermore, the grading indicators of cotton discussed in this paper suggested that the variation and distribution within a cotton sample should be considered in cotton grading, including a parameter redness or blueness (a). Our work would provide a much better approach to measure and evaluate color of cotton.