||We present a mobile application that automatically recognizes art pieces in the subway. Users can take a photo of an art piece with their mobile phones, and by using image recognition our system retrieves information about that particular art piece. By combining the location with image data, we can delimit the dataset of photos of art pieces to speed up the image recognition. The image recognition is based on feature detection using SURF, and by matching feature points using kd-trees for storing the interest points of the training data. We propose a method for selecting good training images when creating the database. In addition, we also cluster the training interest points by the k-means algorithm, which reduces the space of the kd-tree and increase the matching speed. We demonstrate the effectiveness of our approach with an application that allows users to enjoy the art pieces at different subway stations through image recognition.