Optimal texture analysis algorithms for describing degradation of carpets are identified. Experimental design is applied to select from a set of texture analysis algorithms those optimal for identifying texture changes due to degradation of carpets. The degree of wear of a degraded carpet is quantified by comparing its texture to the original texture. The set of texture algorithms is applied on intensity images obtained from the American and the European standards. The performance of the texture algorithms is evaluated using measures that quantify characteristics in the relationship between the metrics and the changes in texture. The statistical analysis of the experimental results shows that the local binary patterns algorithm is optimal in >50% of the cases, for describing degradation of the carpets. Other texture algorithms that optimally characterize the degradation of carpets include the use of the power spectrum, Wigner distribution, and average co-occurrence matrix algorithms.