The authors develop an object recognition system through the combination of 2-D tactile image array and visual sensors. A video camera is used to acquire a top view image of an object and two tactile sensing arrays mounted on a gripper are used to detect tactile information about the lateral surfaces of the object. 3-D reference object models are established as a decision tree, and recognition of unknown objects is accomplished through measuring and comparing input object features with those of the reference objects. The clustering process and recognition procedures are described. The recognition scheme has been implemented, and the resulting decision tree is presented.