This paper describes the work that is done by a group of I3 students at Philips CFT in Eindhoven, Netherlands. I3 is an initiative of Fontys University of Professional Education also located in Eindhoven. The work focuses on the use of computer vision in motion control. Experiments are done with several techniques for object recognition and tracking, and with the guidance of a robot movement by means of computer vision. These experiments involve detection of coloured objects, object detection based on specific features, template matching with automatically generated templates, and interaction of a robot with a physical object that is viewed by a camera mounted on the robot.
This article offers the first substantial survey of the Middle Dutch satire Dit es de Frenesie since the work of C.P. Serrure in the mid nineteenth century. It contests much of the conventional wisdom surrounding De Frenesie, challenging the poem's usual classification as an early boerde or fabliau. Instead it is argued that the text is an experimental work, which blends together elements of several satiric traditions without committing itself to any one. The implications of this maneuver and others within the text are considered, revealing the poem's clear sympathy with the newly educated and articulate laity. De Frenesie itself is appended in both the original Middle Dutch and an English verse translation.
This article deals with automatic object recognition. The goal is that in a certain grey-level image, possibly containing many objects, a certain object can be recognized and localized, based upon its shape. The assumption is that this shape has no special characteristics on which a dedicated recognition algorithm can be based (e.g. if we know that the object is circular, we could use a Hough transform or if we know that it is the only object with grey level 90, we can simply use thresholding). Our starting point is an object with a random shape. The image in which the object is searched is called the Search Image. A well known technique for this is Template Matching, which is described first.
