Abstract Sensing surface textures by touch is a valuable capability for robots. Until recently it w was difficult to bu a compliant sensor with high sennsitivity and high resolution. The GelSight sensor is coompliant and offers sensitivity and resolution exceeding that of the human fingertips. This opens the possibility of measuring and recognizing highly detailed surface texxtures. The GelSight sensor, when pressed against a surfacce, delivers a height map. This can be treated as an image, aand processed using the tools of visual texture analysis. W We have devised a simple yet effective texture recognitioon system based on local binary patterns, and enhanced it by the use of a multi-scale pyramid and a Hellinger ddistance metric. We built a database with 40 classes of taactile textures using materials such as fabric, wood, and sanndpaper. Our system can correctly categorize materials from m this database wit high accuracy. This suggests that the G GelSight sensor ca be useful for material recognition by roobots.