A good accuracy and certainty paper currency recognition has a great signification for banking system as well as for vending machines. In this paper we propose an ultraviolet (UV) Rupiah paper currency image recognition by implementing Gabor wavelet feature extraction. The UV image is used to distinguish between a genuine and a fake paper image currency, since under UV light a different visual in specific areas of the real banknote will glow and show hidden patterns. To have a high accuracy as well as efficiency, we use 3 scales and 8 orientations Gabor bank and subspace-LDA classifier in recognition process. The proposed Gabor method has advantages of easiness and high accuracy. The experimental results demonstrate that this method is quite reasonable in terms of preciseness, with 98.5% overall average recognition rate are obtained for the data of 160 UV Rupiah paper currency images.