Photogrammetria最新文献

The paper describes two cases in which metric information was obtained from single nonmetric photographs. In the first case the relative position of several circular objects such as barrels and wheels was found by a method using their known diameters. This information was very useful in the investigation of an accident. In the second case, the dimensions (radius and height) of a small cylindrical container were found and the photograph was calibrated on the basis of the object's cylindrical shape. This information proved useful in the investigation of a murder case.

The least squares matching method with different window sizes has been investigated in order to find an optimal window size. A variance component model with three different components has been used. A high altitude aerial photographic pair and a close-range photographic pair have been investigated. The experiments have been performed with and without affine parameters as unknowns. In the image material used window sizes smaller than 20 × 20 pixels gave too low a reliablity. When affine parameters are used as unknowns the window size should be larger than 30×30 pixels, for reasons of reliability.

The Adaptive Least Squares Correlation (ALSC), combining gray-level correlation with geometric conditions, was applied to a grid-sampling mode for generation of Digital Terrain Models (DTM) from aerial stereo models.

The heights of targets of different geometric and contrast quality in large-scale digitized images were determined using this technique and compared to results from manual measurements. Both solutions showed an average difference of 0.016–0.038% and a maximum differences of 0.037–0.120% flying height (hg), depending on the height approximation. Most cases investigated required an initial height approximation at the 1–2% hg level. An average height error of 0.2% hg was cleared in each iteration step. The constraints imposed proved to define the movement of the gray-level image patches, thus limiting the search area and probability of false correlation, and increasing the precision and reliability of height determination.

The Craniofacial Research Instrumentation Laboratory at the University of California, San Francisco, has been developing systems for the acquisition and display of biostereometric data. Stereo photographs and X-ray images of the head are used to analyze growth and treatment effects during orthodontic treatment and orthognathic surgery. Recent efforts have been directed towards automating anatomic feature location and tracking on series of time-separated cranial X-rays.

Two tests were performed to evaluate the potential accuracies that could be achieved in feature tracking. In both tests, a series of cranial X-rays was converted to digital images using an array camera [Charge Injection Device (CID)] connected to a real-time video digitizer module or “frame grabber” installed in a microcomputer. The first test series consisted of a single X-ray image which was translated and rotated three times. The second series of images consisted of three actual cranial X-rays of a single subject, acquired over a period of approximately two years.

A number of anatomic features were manually selected on the first image of each series. The features were automatically tracked on subsequent digital images, and their locations compared to those derived from manual digitizing of the original film images.

In this paper, an image segmentation algorithm based upon hierarchical step-wise optimization with a composite merge criterion is presented. In hierarchical step-wise optimization, at each step, the two segments which optimize a criterion/cost function are found and merged. The main innovation proposed in this paper is that different criteria are employed at different stages in the hierarchical process. At the lowest stage, when the segment size is still small, the segment mean is the main information and is used in the merge criterion. For the intermediate stages, with increasing segment size, the mean is no longer sufficient to describe the characteristics of a segment and, therefore, a criterion related to the mean and the variance is considered. At the final stage, additional information, such as the edge information is included in the criterion. In other words, with increasing segment size, more information is required to describe the characteristics of the segments and is incorporated into a composite criterion. Experimental results on a Landsat image show that improved segmentations can result when a composite criterion is employed.

Photogrammetric monitoring of displacements requires repetitive photography. The conventional mensuration scheme of targetted and natural points, and inherent problems are briefly discussed. An integrated measuring system using the computer-controlled capabilities of the analytical stereo-plotter OMI AP-2C is described and applied. This on-line mode of operations increases the speed of execution, enhances the quality of data, offers editing capabilities and increases flexibility.

Systematic errors introduced through film deformation constitute a major factor limiting the photogrammetric accuracy of non-metric images. This paper examines the effectiveness of multiple exposure photography in reducing that component of the object-point positioning bias which is due to film unflatness. Aspects of network precision and accuracy are discussed, as are details concerning the additional parameter model selection and the use of orientation constraints. A non-metric camera experiment, in which multiple exposures were employed, is outlined and the results of this practical application are presented.