Lower-limb robotic prosthetics can benefit from context awareness to provide comfort and safety to the amputee. In this work, we developed a terrain identification and surface inclination estimation system for a prosthetic leg using visual and inertial sensors. We built a dataset from which images with high sharpness are selected using the IMU signal. The images are used for terrain identification and inclination is also computed simultaneously. With such information, the control of a robotized prosthetic leg can be adapted to changes in its surrounding.