Computerised stereoscopic measurement of the human retina

The research described herein is an investigation into the problems of obtaining useful clinical measurements from stereo photographs of the human retina through automation of the stereometric procedure by digital stereo matching and image analysis techniques. Clinical research has indicated a correlation between physical changes to the optic disc topography (the region on the retina where the optic nerve enters the eye) and the advance of eye disease such as hypertension and glaucoma. Stereoscopic photography of the human retina (or fundus, as it is called) and the subsequent measurement of the topography of the optic disc is of great potential clinical value as an aid in observing the pathogenesis of such disease, and to this end, accurate measurements of the various parameters that characterise the changing shape of the optic disc topography must be provided. Following a survey of current clinical methods for stereoscopic measurement of the optic disc, fundus image data acquisition, stereo geometry, limitations of resolution and accuracy, and other relevant physical constraints related to fundus imaging are investigated. A survey of digital stereo matching algorithms is presented and their strengths and weaknesses are explored, specifically as they relate to the suitability of the algorithm for the fundus image data. The selection of an appropriate stereo matching algorithm is discussed, and its application to four test data sets is presented in detail. A mathematical model of two-dimensional image formation is developed together with its corresponding auto-correlation function. In the presense of additive noise, the model is used as a tool for exploring key problems with respect to the stereo matching of fundus images. Specifically, measures for predicting correlation matching error are developed and applied. Such measures are shown to be of use in applications where the results of image correlation cannot be independently verified, and meaningful quantitative error measures are required. The application of these theoretical tools to the fundus image data indicate a systematic way to measure, assess and control cross-correlation error. Conclusions drawn from this research point the way forward for stereo analysis of the optic disc and highlight a number of areas which will require further research. The development of a fully automated system for diagnostic evaluation of the optic disc topography is discussed in the light of the results obtained during this research

Integration of 3D vision based structure estimation and visual robot control

Enabling robot manipulators to manipulate and/or recognise arbitrarily placed 3D objects under sensory control is one of the key issues in robotics. Such robot sensors should be capable of providing 3D information about objects in order to accomplish the above mentioned tasks. Such robot sensors should also provide the means for multisensor or multimeasurement integration. Finally, such 3D information should be efficiently used for performing desired tasks. This work develops a novel computational frame wo rk for solving some of these problems. A vision (camera) sensor is used in conjunction with a robot manipulator, in the frame-work of active vision to estimate 3D structure (3D geometrical model) of a class of objects. Such information is used for the visual robot control, in the frame-work of model based vision. One part o f this dissertation is devoted to the system calibration. The camera and eye/hand calibration is presented. Several contributions are introduced in this part, intended to improve existing calibration procedures. This results in more efficient and accurate calibrations. Experimental results are presented. Second part of this work is devoted to the methods of image processing and image representation. Methods for extracting and representing necessary image features comprising vision based measurements are given. Third part of this dissertation is devoted to the 3D geometrical model reconstruction of a class o f objects (polyhedral objects). A new technique for 3D model reconstruction from an image sequence is introduced. This algorithm estimates a 3D model of an object in terms of 3D straight-line segments (wire-frame model) by integrating pertinent information over an image sequence. The image sequence is obtained from a moving camera mounted on a robot arm. Experimental results are presented. Fourth part of this dissertation is devoted to the robot visual control. A new visual control strategy is introduced. In particular, the necessary homogeneous transformation matrix for the robot gripper in order to grasp an arbitrarily placed 3D object is estimated. This problem is posed as a problem of 3D displacement (motion) estimation between the reference model of an object and the actual model of the object. Further, the basic algorithm is extended to handle multiple object manipulation and recognition. Experimental results are presented

The use of multiple cameras and geometric constraints for 3-D measurement

This thesis addresses some of the problems involved in the automation of 3-D photogrammetric measurement using multiple camera viewpoints. The primary research discussed in this thesis concerns the automatic solution of the correspondence problem. This and associated research has led to the development of an automated photograrnmetric measuring system which combines the techniques from both machine vision and photogrammetry. Such a system is likely to contribute greatly to the accessibility of 3-D measurement to non-photogrammetrists who will generally have little knowledge and expertise of photogrammetry. A matching method, which is called the 3-D matching method, is developed in the thesis. This method is based on a 3-D intersection and "epipolar plane", as opposed to the 2-D intersection of the epipolar line method. The method is shown to provide a robust and flexible procedure,especially where camera orientation parameters are not well known. The theory of the method is derived and discussed. It is further developed by combination with a bundle adjustment process to iteratively improve the estimated camera orientations and to gradually introduce legitimate matched target images from multiple cameras. The 3-D target matching method is also optimised using a 3-D space constrained search technique. A globally consistent search is developed in which pseudo target images are defined to overcome problems due to occlusion. Hypothesis based heuristic algorithms are developed to optimise the matching process. This method of solving target correspondences is thoroughly tested and evaluated by simulation and by its use in practical applications. The characteristics of the components necessary for a photogrammetric measuring system are investigated. These include sources of illumination, targets, sensors, lenses, and framegrabbers. Methods are introduced for analysis of their characteristics. CCD cameras are calibrated using both plumb line and self calibration methods. These methods provide an estimation of some of the sources of error, which influence the performance of the system as a whole. The design of an automated photogrammetric measuring system with a number of novel features is discussed and a prototype system is developed for use in a constrained environment. The precision, accuracy, reliability, speed, and flexibility of the developed system are explored in a number of laboratory and experimental applications. Trials show that with further development the system could have commercial value and be used to provide a solution suitable for photogrammetrists and trained operators in a wide range of applications