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.
Due to the prominent place composition holds in teaching French
to non-native speakers, this article examines the effectiveness of
formative evaluation in improving the writing skills of second year
students in the department of French language. I
n addition, by
showing the difference in the scoring results between the students
who followed the formative evaluation and those who didn’t, this
article aims to illustrate the impact of distributing copies of the
grading scale to students during the training period.
