When robots walk on uneven terrain, trajectory planning should take into account both the whole-body dy-namics and the ground geometry simultaneously. In uneven terrain environments, there are only a limited number of places where the robot is able to make stable contact with the ground without its feet wobbling or slipping because of the intricate round geometry. In such environments, the optional landing position and time to maintain the robot's balance and stable foot contact are not obvious and computationally expensive. In this study, we propose a robust walking system that integrates environment recognition using steppable regions and walking control for a humanoid robot to walk on uneven terrain. In this paper, a steppable region is defined as a two-dimensional convex hull that represents a region where a robot is capable of landing. We propose a method to compute the steppable region quickly by 2.SD projection of the environment points and spatial filtering. In this system, the walking controller integrates the steppable region with the Capture Region to modify the landing position from a two-dimensional geometric calculation. In addition, to cope with the environment recognition error, we have introduced a trajectory generation that allows the feet to penetrate the ground and hybrid control of position and torque. We verified the effectiveness of the proposed system through experiments in which a life-size humanoid robot walked on uneven terrain and recovered when pushed.