Vision allows a robotic system to obtain geometrical and qualitative information on the surrounding environment to be used both for motion planning and control. In particular, control based on feedback of visual measurements is called visual servoing. In the first part of this chapter, some basic algorithms for image processing, aimed at extracting numerical information referred to as image features, are presented. This information, regarding images of objects present in the camera view, can be used to estimate the relative pose of the camera with respect to a target. To this end, analytic pose estimation methods, based on the measurement of a certain number of points of the target or correspondences, are presented. In addition, numerical pose estimation methods are introduced, based on the integration of the linear mapping between the camera velocity and the time derivative of the image features. Then, the two main approaches to visual servoing are considered, namely position-based visual servoing and image-based visual servoing. If multiple views of the same scene are available, additional information can be obtained using stereo vision techniques and epipolar geometry. Moreover, hybrid visual servoing methods can be adopted, which combine the benefits of image-based and position-based approaches. The chapter ends with the presentation of a conceptual solution to the problem of camera calibration.