1,264 research outputs found
3D discrete rotations using hinge angles
International audienceIn this paper, we study 3D rotations on grid points computed by using only integers. For that purpose, we investigate the intersection between the 3D half-grid and the rotation plane. From this intersection, we define 3D hinge angles which determine a transit of a grid point from a voxel to its adjacent voxel during the rotation. Then, we give a method to sort all 3D hinge angles with integer computations. The study of 3D hinge angles allows us to design a 3D discrete rotation and to estimate the rotation between a pair of digital images in correspondence
Incremental and Transitive Discrete Rotations
A discrete rotation algorithm can be apprehended as a parametric application
from \ZZ[i] to \ZZ[i], whose resulting permutation ``looks
like'' the map induced by an Euclidean rotation. For this kind of algorithm, to
be incremental means to compute successively all the intermediate rotate d
copies of an image for angles in-between 0 and a destination angle. The di
scretized rotation consists in the composition of an Euclidean rotation with a
discretization; the aim of this article is to describe an algorithm whic h
computes incrementally a discretized rotation. The suggested method uses o nly
integer arithmetic and does not compute any sine nor any cosine. More pr
ecisely, its design relies on the analysis of the discretized rotation as a
step function: the precise description of the discontinuities turns to be th e
key ingredient that will make the resulting procedure optimally fast and e
xact. A complete description of the incremental rotation process is provided,
also this result may be useful in the specification of a consistent set of
defin itions for discrete geometry
Print-Scan Resilient Text Image Watermarking Based on Stroke Direction Modulation for Chinese Document Authentication
Print-scan resilient watermarking has emerged as an attractive way for document security. This paper proposes an stroke direction modulation technique for watermarking in Chinese text images. The watermark produced by the idea offers robustness to print-photocopy-scan, yet provides relatively high embedding capacity without losing the transparency. During the embedding phase, the angle of rotatable strokes are quantized to embed the bits. This requires several stages of preprocessing, including stroke generation, junction searching, rotatable stroke decision and character partition. Moreover, shuffling is applied to equalize the uneven embedding capacity. For the data detection, denoising and deskewing mechanisms are used to compensate for the distortions induced by hardcopy. Experimental results show that our technique attains high detection accuracy against distortions resulting from print-scan operations, good quality photocopies and benign attacks in accord with the future goal of soft authentication
Combinatorial Gradient Fields for 2D Images with Empirically Convergent Separatrices
This paper proposes an efficient probabilistic method that computes
combinatorial gradient fields for two dimensional image data. In contrast to
existing algorithms, this approach yields a geometric Morse-Smale complex that
converges almost surely to its continuous counterpart when the image resolution
is increased. This approach is motivated using basic ideas from probability
theory and builds upon an algorithm from discrete Morse theory with a strong
mathematical foundation. While a formal proof is only hinted at, we do provide
a thorough numerical evaluation of our method and compare it to established
algorithms.Comment: 17 pages, 7 figure
Automatic alignment for three-dimensional tomographic reconstruction
In tomographic reconstruction, the goal is to reconstruct an unknown object
from a collection of line integrals. Given a complete sampling of such line
integrals for various angles and directions, explicit inverse formulas exist to
reconstruct the object. Given noisy and incomplete measurements, the inverse
problem is typically solved through a regularized least-squares approach. A
challenge for both approaches is that in practice the exact directions and
offsets of the x-rays are only known approximately due to, e.g. calibration
errors. Such errors lead to artifacts in the reconstructed image. In the case
of sufficient sampling and geometrically simple misalignment, the measurements
can be corrected by exploiting so-called consistency conditions. In other
cases, such conditions may not apply and we have to solve an additional inverse
problem to retrieve the angles and shifts. In this paper we propose a general
algorithmic framework for retrieving these parameters in conjunction with an
algebraic reconstruction technique. The proposed approach is illustrated by
numerical examples for both simulated data and an electron tomography dataset
Scale Invariant Interest Points with Shearlets
Shearlets are a relatively new directional multi-scale framework for signal
analysis, which have been shown effective to enhance signal discontinuities
such as edges and corners at multiple scales. In this work we address the
problem of detecting and describing blob-like features in the shearlets
framework. We derive a measure which is very effective for blob detection and
closely related to the Laplacian of Gaussian. We demonstrate the measure
satisfies the perfect scale invariance property in the continuous case. In the
discrete setting, we derive algorithms for blob detection and keypoint
description. Finally, we provide qualitative justifications of our findings as
well as a quantitative evaluation on benchmark data. We also report an
experimental evidence that our method is very suitable to deal with compressed
and noisy images, thanks to the sparsity property of shearlets
Multiresolutional Fault-Tolerant Sensor Integration and Object Recognition in Images.
This dissertation applies multiresolution methods to two important problems in signal analysis. The problem of fault-tolerant sensor integration in distributed sensor networks is addressed, and an efficient multiresolutional algorithm for estimating the sensors\u27 effective output is proposed. The problem of object/shape recognition in images is addressed in a multiresolutional setting using pyramidal decomposition of images with respect to an orthonormal wavelet basis. A new approach to efficient template matching to detect objects using computational geometric methods is put forward. An efficient paradigm for object recognition is described
Wallpaper Maps
A wallpaper map is a conformal projection of a spherical earth onto regular polygons with which the plane can be tiled continuously. A complete set of distinct wallpaper maps that satisfy certain natural symmetry conditions is derived and illustrated. Though all of the projections have been published before, the family had not been characterized as a whole. Some wallpaper maps generalize to one-parameter subfamilies in which the sphere is pre-transformed by a conformal automorphism
Multi-step approach for automated scaling of photogrammetric micro-measurements
[EN] Photogrammetry can be used for the measurement of small objects with micro-features, with good results, low costs, and the possible addition of texture information to the 3D models. The performance of this technique is strongly affected by the scaling method, since it retrieves a model that must be scaled after its elaboration. In this paper, a fully automated multi-step scaling system is presented, which is based on machine vision algorithms for retrieving blurred areas. This method allows researchers to find the correct scale factor for a photogrammetric micro model and is experimentally compared to the existing manual method basing on the German guideline VDI/VDE 2634, Part 3. The experimental tests are performed on millimeter-sized certified workpieces, finding micrometric errors, when referred to reference measurements. As a consequence, the method is candidate to be used for measurements of micro-features. The proposed tool improves the performance of the manual method by eliminating operator-dependent procedures. The software tool is available online as supplementary material and represents a powerful tool to face scaling issues of micro-photogrammetric activities.Frangione, A.; Sánchez Salmerón, AJ.; Modica, F.; Percoco, G. (2019). Multi-step approach for automated scaling of photogrammetric micro-measurements. The International Journal of Advanced Manufacturing Technology. 102(1-4):747-757. https://doi.org/10.1007/s00170-018-03258-w7477571021-
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