Thyroid nodule is a kind of frequently-occurring disease. Ultrasound technology is the preferred examination method for the disease. Extracting the texture feature distinguishing the benign and malignancy in the ultrasound images and discriminate them has a wide prospect of clinical application. Dual-tree complex wavelet transform (DT-CWT) and Gabor wavelet are the important approaches to texture feature extraction. Here, we present an approach of thyroid nodules recognition by fusing multi-scale DT-CWT and Gabor wavelet features. Firstly, we use Gaussian pyramid to decompose the thyroid ultrasound image into multi-scale space. Followed by extracting DT-CWT and Gabor multi-scale features, the feature fusion is performed. Support vector machine (SVM) is applied to classify so as to verify the effectiveness of the proposed method. Experimental results show that the proposed method can achieve a high recognition rate.