Forgery note recognition plays an important role in our daily life as the general public has an opportunity to receive the forgery notes. This paper proposes a big data and cloud based wearable forgery note recognition system. First, a wearable camera is employed for taking the note images. Then, the note images are sent to the cloud systems. There is a big data system in the cloud server. Image features are extracted based on the coutourlet transform. The coutourlet transform is employed for the feature extraction because the contourlet has the multi-resolution property as well as performs the local and directional image decomposition. In particular, the statistical information of the coefficients obtained by performing the contourlet transform is employed as the features. Then, a support vector machine is used for performing the forgery note recognition. Extensive computer numerical simulations are performed. The obtained results show that the proposed method achieves a higher accuracy rate compared to the existing methods.