A graphical user interface program was created along with shape models, which allow persons with disabilities to set up a stereovision system with off-the-shelf hardware and detect objects of interest, which can be picked up using a sensor assisted telerobotic manipulator. A Hitachi KP-D50 CCD camera and an Imaging Source CCD camera were used along with two Imaging Source DFG/LC1 frame grabbers to set up a stereovision system. In order to use the stereovision system, the two main problems of correspondence and reconstruction are solved using subroutines of the program created for this work.The user interface allows the user to easily perform the intrinsic and extrinsic camera calibration required for stereovision, by following a few basic steps incorporated into the user interface program, which are described in this thesis. A calibration table required for these tasks can also be easily created using the program. In order to detect the object of interest, shape models, created by the user interface program, are used to solve the correspondence problem of stereovision. The correspondence problem is that of locating corresponding points in the left eye and the right eye, which are necessary to perform the calculations to obtain the location of the object of interest with respect to the end-effector. The shape models created for some commonly available items such as a doorknob and a door handle are included in the program and used to test the stereovision system. As expected, the error of detection decreases as the stereo system is moved closer to the object of interest in the x-, y- and z-position.

Wavelets are functions used to approximate data and can be traced back to several different areas, including seismic geology and quantum mechanics. Wavelets are applicable in many areas, including fingerprint and data compression, earthquake prediction, speech discrimination, and human vision. In this paper, we first give a brief history on the origins of wavelet theory. We will then discuss the work of Daubechies, whose construction of continuous, compactly supported scaling functions resulted in an explosion in the study of wavelets in the 1990's. These scaling functions allow for the construction of Daubechies' wavelets. Next, we shall use the algorithm to construct the Daubechies D4 scaling filters associated with the D4 scaling function. We then explore the Cascade Algorithm, which is a process that uses approximations to get possible representations for the D2N scaling function of Daubechies. Lastly, we will use the Cascade Algorithm to get a visual representation of the D4 scaling function.