This paper presents a novel approach to object recognition using a reconfigurable gripper with multiple time-of-flight (ToF) sensors attached to the fingers and palm, introducing the concept of noncontact tactile perception. This approach aims to promote aproprioceptive sense in the gripper workspace, allowing object prediction in manipulation tasks. The Hybrid-Active (H-A) gripper can adapt its topology to achieve different object reading points to generate a reliable object estimation. Non-contact tactile perception uses ToF sensors and gripper reconfiguration degrees-of-freedom for 3D perception and surface estimation of the pick-up object. This method is based on five ToF sensors in the palm that identify the distance and adjust the gripper to the center of the object through its capability to manage the manipulator. The H-A gripper also has twelve sensors distributed over its three fingers: four sensors on each finger, two on the distal phalanx, and two on the middle phalanx. Fingers have a rotational mobility of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$180^{\circ }$</tex-math></inline-formula> , allowing the sensing of all faces of the object at different angles for the three-dimensional reconstruction. The proposed approach was evaluated in four experiments that analyzed the influence of resolution, object complexity, finger tilt, and angular sampling over 13 objects with different complexities. The experimentation set allows the overall evaluation of non-contact tactile perception and the specification of its performance parameters.