Autonomous mobile robots need to move in an outdoor environment changing daily. Recently, simultaneous localization and mapping (SLAM) is often used for an autonomous mobile robot navigation. This method has good performance, but it takes time and effort to create accurate maps. However, considering the case of human, human do not need such accurate maps. Our previous study of human environmental recognition ability demonstrated that human uses scenery and road information. In this study, we propose an autonomous mobile navigation method with image processing based on human environmental recognition ability. This method uses GIST feature for localization, and SegNet for road detection. We validated our method in outdoor using a mobile robot. Experimental results demonstrate that the proposed method enables autonomous mobile navigation without accurate map.