Since the present performance of smartphone based personal indoor localization is still far from satisfaction with problems in accuracy, cost and etc., a duel-step filtering indoor localization algorithm fusing Wi-Fi fingerprints and images implemented on devices like smartphones was proposed in this paper. This algorithm comprised of offline stage and online stage. On the offline stage, Wi-Fi fingerprints were collected and a fingerprint library sampled in different positions in the coordinate system was constructed. Photos were taken in that stage to extract the image features. On the online stage, the first filter process was to determine the possible area where the user is currently by using Wi-Fi information captured in real-time. Then a distance compensation algorithm was proposed in this paper to extract features of the real-time image taken by the user to determine the exact localized position. Experimental results show that this algorithm can effectively improve localization precision compared with traditional Wi-Fi and image based localization methods in environments with fewer APs (Access Points) and similar layouts, thus is capable for general localization or LBS (Location-Based Service) relevant applications.