This study aims is to analyze the effect of spatial accuracy of the control points on the
images geometric correction accuracy, and this is done by applying tests on the same
image (IKONOS), where polynomial transformations were applied using sets
of control
points, each with absolute accuracy different from the other. These points were
extrapolated from a 1/1000 topographic map and from a georeferenced MOMS satellite
image with geometric accuracy of 2m and measured by GPS. The study showed that it is
possible to obtain the most accurate geometric correction by using control points with
absolute accuracy close to the spatial resolution of the image. It also showed that the use of
more precise control points would not ameliorate the accuracy of the geometric correction,
because the measurement of these points on the image is limited by its spatial resolution.
The geometric correction of remote sensing images becomes a key issue in
production and updating digital maps, multisource data integration, management and
analysis for many geomatic applications. 2D polynomial functions are the most prevalent
to
achieve this correction.
Previous researches have shown that the application of 2D polynomials is
conditioned by the planarity of the terrain and the uniform distribution of ground control
points, but did not explicitly discuss the criteria for evaluating the success or failure of
their application. In this study, we will try to give some of these criteria and to develop
some old analog cartographic rules to suit the nature of the digital satellite images.
In this research, we discussed mathematical foundation for evaluating the precision
of control points- based geometric correction of satellite images. We have also tested the
effect of the topography of the imaged scene on this accuracy. The test has been carried out
by the use of satellite images extracted from Google Earth. These images cover some areas
in the city of Latakia in Syria. Also, control points have been extracted from Google Earth
and transformed into the Syrian stereographic coordinates system.
Results demonstrated that the second degree 2D polynomial is very suitable for plan
small scenes with uniform distribution of the control points over the entire scene.
There are many sources that cause the emergence of geometric deformations in close
range images. These deformations are accumulated and not present singly in the image.
Therefore, it is necessary to rectify (correct) the image before extracting geo
metric or
semantic data from it.
Two methods are available to rectify the close range images. These ones are the
parametric and the non-parametric methods. Non-parametric approach does not require
knowledge of the parameters of the used camera. Control points and geometric
transformations are considered as the two main components in the non-parametric
approach.
Usually, barrel and perspective deformations are present in close range images. In
this paper, we will study the impact of the distribution of control points and the degree of
geometric transformation on the correction of the image of these deformations. The test
was performed using a close range image of a historical façade. This image was exposed to
previous deformations by simulation. The goal is to investigate the effect of the
distribution of control points and on the effectiveness of global (linear) and local
transformations used to rectify the close range images. It has been demonstrated that the
control points located in different parts of the image have different deformation rates, the
control points distributed in the center of the image suffers less deformations, and local
transformations give the best results when rectifying images with complex deformations.
Bacteriological critical control points (CCPS) for automatic ice cream
industry were identified based on the primary ingradients of such industry,
processing stages and working environment.
Three thousand samples were analyzed during two productio
n seasons.
There were four critical control points in the company in which the study
was conducted, Pasteurization (mix) stage, cold (tanks) stage, freezing stage,
and hardning (tunnel) stage. The end-product did not coincide with the Syrian
standard because of these critical control point, which contributed by 15%,
25%, 35% and 25% respectively, meanwhile the remaining pointes, such as the
used water, choclate, air and workers were not critical control points under the
production conditions of the investigated company.
