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Pick and place tasks are one of the most typical applications in robotics. Conventional robots perform a fixed task which restricts the workspace in terms of flexibility. With development in mobile robotics [1] and automation it is necessary to introduce sensor systems that enable a more flexible approach. This paper demonstrates a computer vision system which uses a colour-based approach to object detection and estimation of its 3D world coordinates based on a 2D image. The system is used to enable a robot arm to pick up an object and place it on a CNC-mill. Based on the use case the vision system can tell the robot if an object has been detected and where it is relatively to the camera. Using the robot operating system (ROS) and OpenCv, image thresholding is performed for detecting the object. The Canny edge detection algorithm is deployed to mark the object with a bounding box. The retrieved information from those operations is used for the 3D pose estimation. Using a linear calibration, the error of the system can be reduced, which results in an accuracy of 0.09cm. [ABSTRACT FROM AUTHOR]