This paper addresses the problem of photo time-stamp detection and recognition, which is to determine the time a photo was taken. Since the time-stamp is exposed together with the scene, the main challenge comes from complex background and saturation of the time-stamp. An MAP (Maximum a posterior probability) based template matching method is proposed to detect and recognize the time-stamp simultaneously from a photo. A key step of this method is skeleton-matching algorithm for individual digit, which supports partial matching and deals with complex background and saturation. Practically, to avoid exhaustive search, a saliency map is obtained by applying a set of morphologic operators on a photo. Proposals can be generated from the saliency map and the proposed method calculates the probability for each proposal. An application with strong prior knowledge is also given in which the proposed method achieves high accuracy in almost real time.