The conspicuity of different targets in image sequences taken by approaching sensors is addressed in applications such
as the assessment of camouflage effectiveness or the performance evaluation of autonomous systems. In such evaluation
processes the consideration of background characteristics is essential due to the propensity to confuse target and
background signatures. Several discriminating features of target and background signature can be derived. Furthermore,
the changing aspect and spatial resolution during an approach on a target have to be taken into account.
Considering salient points in image sequences, we perform a nominal/actual value comparison by evaluating the receiver
operating characteristic (ROC) curve for the detections in each image. Hence, reference regions for targets and
backgrounds are provided for the entire image sequence by means of robust image registration. The consideration of the
uncertainty for the temporal progression of the ROC curve enables hypothesis testing for well-founded statements about
the significance of the determined distinctiveness of targets with respect to their background. The approach is neither
restricted to images taken by IR sensors nor applicable to low level image analysis steps only, but can be considered as a
general method for the assessment of feature evaluation and target distinctiveness.
The analysis method proposed facilitates an objective comparison of object appearance with both, its relevant
background and other targets, using different image analysis features. The feasibility and the usefulness of the approach
are demonstrated with real data recorded with a FLIR sensor during a field trial on a bare and mock-up target.
We present a strategy to determine shrinked rotation-symmetric aspheres. First, we approximate nonlinearly a
conic based on a direct least squares start-solution with quadratic constraint to a set of datapoints. Afterwards,
we smooth aspheres polynomially.
The requirements of optical surfaces are increasing with respect to their functionality and accuracy of form. Furthermore, it is a goal for the optical industry to unify the lens process from development to production. In our phase of design we have an arbitrary set of 3D-points of a free formed surface. With approximation through NURBS, we get a continuous description of this surface. To the generated NURB-Spline, we have developed a CNC-program for the UPM-3000 machine, which drives the cutter along the level curve. Therefore, we triangulate the NURBS-surface. By the desired accuracy and the generated triangles, we determine levels of the surface. Thus, we refine the given triangulation. Hence we have a triangular decomposition for each level, which will be driven along by the cutter. The described method will be compared to the common raster-fly-cut-method for accuracy and cutting time.
The LINOS Photonics company has developed a new tactile sensor to measure aspheric surfaces. The sensing device drives along spherical coordinates and the measuring data of a level curve is obtained by the rotation of the lens. The complete asphere of the lens is reconstructed by a number of such level curves. All data is given in a spherical coordinate system. The company provides a software to determine the error between the actual surface and a reference asphere with respect to a cartesian coordinate system. But the algorithm depends on the strong assumption that the peak of the reconstructed asphere is equal to the rotational point of the measuring instrument. Our algorithm expands the existing method. We minimize the distance of the reference asphere to the measuring points in a cartesian coordinate system. To do this, we calculate the optimal rotation and translation of the reference asphere
to the measured points. This defines a non-linear optimization problem, which is solved with algorithm of Levenberg and Marquardt. Furthermore, we are able to calculate the Jacobi matrix with
respect to the rotation center. The output of the proposed algorithms contains the maximal deviation for each measuring point in z-direction and the variance of the error. Additionally, we determine a pseudo tangential deviation between the reference and the actual geometry by a secant method. Altogether the new algorithm enables us to deliver comparable results for the asphere measuring problem.
A hybrid phase unwrapping algorithm has been proposed recently, which uses a window-based technique and two local phase unwrapping approaches to determine gradient information for each window. However, with this approach, in many practical applications, we encountered certain inconsistencies, e.g. caused by noise in the input phase map. In this paper, we present an improved window-based algorithm for unwrapping noisy phase maps. With pixel-based images, we can only obtain residues of charge one, but, with this new method, higher charges are possible. Eventually the total charge of positive and negative residues may be unequal. Therefore, we extend the set of residues by border residues until we obtain equal charges. We build connected components containing neighbors of residues using the breath-first-search method. Hereafter, we follow a minimum-cost graph-theory method determining the set of branch-cuts and computing the global minimum of the total cut-length. Every positive residue is associated to a corresponding negative residue. We connect these pairs by the path with the worst overlap error obtained by one of the local phase unwrapping approaches. Using this new method, we are able to reduce the rms-phase-error by factor 5, when comparing the results to the existing hybrid phase unwrapping algorithm.