The robustness of textural features on speckle noise is of vital importance for ultrasound imaging. A set of novel fuzzy features for thyroid ultrasound texture representation, demonstrating noise-resistant properties, is presented, analyzed and evaluated in this study. The textural feature extraction scheme is based on the fuzzyfication of the local binary pattern approach. The proposed features are evaluated on an annotated dataset of B-mode thyroid ultrasound images acquired from 75 patients. The experimental results illustrate that these features provide accurate representation of the thyroid texture. They can be effectively utilized for thyroid nodule detection outperforming other thyroid texture representation approaches that have been recently proposed in the literature.