This paper addresses the problem of robotic visual servoing (eye-in-hand configuration) around a static rigid target. The objective is to move the image projections of certain feature points of the static rigid target to some desired image positions. The eye-in-hand configuration consists of a CCD camera mounted on the end-effector of the robotic manipulator to provide visual measurements of the motion of the target's features. The vision algorithm is based on a cross-correlation technique, called SSD optical flow. The camera model introduces a number of parameters that must be estimated on-line. An adaptive control algorithm compensates for the servoing errors and the computational delays which are introduced by the time-consuming vision algorithms. Stability issues along with issues concerning the minimum number of required feature points are discussed. Experimental results are presented to verify the validity and the efficacy of the proposed algorithms.