Image recapture detection (IRD) is to distinguish real-scene images from the recaptured ones. Being able to detect recaptured images, a single image based counter-measure for rebroadcast attack on a face authentication system becomes feasible. Being able to detect recaptured images, general object recognition can differentiate the objects on a poster from the real ones, so that robot vision is more intelligent. Being able to detect recaptured images, composite image can be detected when recapture is used as a tool to cover the composite clues. As more and more methods have been proposed for IRD, an open database is indispensable to provide a common platform to compare the performance of different methods and to expedite further research and collaboration in the field of IRD. This paper describes a recaptured image database captured by smart phone cameras. The cameras of smart phones represent the middle to low-end market of consumer cameras. The database includes real-scene images and the corresponding recaptured ones, which targets to evaluate the performance of image recapture detection classifiers as well as provide a reliable data source for modeling the physical process to obtain the recaptured images. There are three main contributions in this work. Firstly, we construct a challenging database of recaptured images, which is the only publicly open database up to date. Secondly, the database is constructed by the smart phone cameras, which will promote the research of algorithms suitable for consumer electronic applications. Thirdly, the contents of the real-scene images and the recaptured images are in pair, which makes the modeling of the recaptured process possible.