109 research outputs found
3D functional models of monkey brain through elastic registration of histological sections
In this paper we describe a method for the reconstruction and visualization of functional models of monkey brains. Models are built through the registration of high resolution images obtained from the scanning of histological sections with reference photos taken during the brain slicing. From the histological sections it is also possible to acquire specifically activated neuron coordinates introducing functional information in the model. Due to the specific nature of the images (texture information is useless and the sections could be deformed when they were cut and placed on glass) we solved the registration problem by extracting corresponding cerebral cortex borders (extracted with a snake algorithm), and computing from their deformation an image transform modeled as an affine deformation plus a non-linear field evaluated as an elastically constrained deformation minimizing contour distances. Registered images and contours are used then to build 3D models of specific brains by a software tool allowing the interactive visualization of cortical volumes together with the spatially referenced neurons classified and differently colored according to their functionalities
Intensity-based image registration using multiple distributed agents
Image registration is the process of geometrically aligning images taken from different sensors, viewpoints or instances in time. It plays a key role in the detection of defects or anomalies for automated visual inspection. A multiagent distributed blackboard system has been developed for intensity-based image registration. The images are divided into segments and allocated to agents on separate processors, allowing parallel computation of a similarity metric that measures the degree of likeness between reference and sensed images after the application of a transform. The need for a dedicated control module is removed by coordination of agents via the blackboard. Tests show that additional agents increase speed, provided the communication capacity of the blackboard is not saturated. The success of the approach in achieving registration, despite significant misalignment of the original images, is demonstrated in the detection of manufacturing defects on screen-printed plastic bottles and printed circuit boards
Fast Mesh-Based Medical Image Registration
In this paper a fast triangular mesh based registration method is proposed.
Having Template and Reference images as inputs, the template image is
triangulated using a content adaptive mesh generation algorithm. Considering
the pixel values at mesh nodes, interpolated using spline interpolation method
for both of the images, the energy functional needed for image registration is
minimized. The minimization process was achieved using a mesh based
discretization of the distance measure and regularization term which resulted
in a sparse system of linear equations, which due to the smaller size in
comparison to the pixel-wise registration method, can be solved directly. Mean
Squared Difference (MSD) is used as a metric for evaluating the results. Using
the mesh based technique, higher speed was achieved compared to pixel-based
curvature registration technique with fast DCT solver. The implementation was
done in MATLAB without any specific optimization. Higher speeds can be achieved
using C/C++ implementations.Comment: Accepted manuscript for ISVC'201
Color image registration under illumination changes
The estimation of parametric global motion has had a significant attention
during the last two decades, but despite the great efforts invested, there
are still open issues. One of the most important ones is related to the ability to recover
large deformation between images in the presence of illumination changes
while kipping accurate estimates. Illumination changes in color images are another
important open issue. In this paper, a Generalized least squared-based motion
estimator is used in combination with color image model to allow accurate
estimates of global motion between two color images under the presence of large
geometric transformation and illumination changes. Experiments using challenging
images have been performed showing that the presented technique is feasible
and provides accurate estimates of the motion and illumination parameter
Automatic Optimization of Alignment Parameters for Tomography Datasets
As tomographic imaging is being performed at increasingly smaller scales, the stability of the scanning hardware
is of great importance to the quality of the reconstructed image. Instabilities lead to perturbations in the
geometrical parameters used in the acquisition of the projections. In particular for electron tomography
and high-resolution X-ray tomography, small instabilities in the imaging setup can lead to severe artifacts.
We present a novel alignment algorithm for recovering the true geometrical parameters \emph{after} the object
has been scanned, based on measured data.
Our algorithm employs an optimization algorithm that combines alignment with reconstruction.
We demonstrate that problem-specific design choices made in the implementation are vital to the success of the method. The algorithm
is tested in a set of simulation experiments. Our experimental results indicate that the method is capable of
aligning tomography datasets with considerably higher accuracy compared to standard cross-correlation methods
Advances in multispectral and hyperspectral imaging for archaeology and art conservation
Multispectral imaging has been applied to the field of art conservation and art history since the early 1990s. It is attractive as a noninvasive imaging technique because it is fast and hence capable of imaging large areas of an object giving both spatial and spectral information. This paper gives an overview of the different instrumental designs, image processing techniques and various applications of multispectral and hyperspectral imaging to art conservation, art history and archaeology. Recent advances in the development of remote and versatile multispectral and hyperspectral imaging as well as techniques in pigment identification will be presented. Future prospects including combination of spectral imaging with other noninvasive imaging and analytical techniques will be discussed
Registro semiautomático entre imagens infravermelhas e RGB coletadas por um par de câmaras digitais
A utilização de imagens adquiridas por sensores CCDs de médio formato, em plataformas aéreas, é uma alternativa para a redução de custos de projetos de aerolevantamento. Porém, a utilização de sensores que captem somente a banda do visÃvel (RGB) restringe algumas aplicações, tornando-se relevante integrar um sensor adicional que capte o infravermelho próximo (IR). No mercado há várias soluções para a aquisição simultânea de várias bandas espectrais. Uma alternativa que possibilita uma redução nos custos de integração é coletar as bandas RGB com uma câmara e a infravermelha com uma segunda câmara. É necessário, então, registrar as imagens, o que implica em determinar um conjunto de pontos ou feições correspondentes, calcular uma função de mapeamento polinomial e reamostrar uma das imagens. Um dos problemas mais crÃticos é a determinação de correspondência entre as imagens, devido à s diferenças radiométricas entre as imagens. Neste trabalho são utilizadas técnicas de detecção de pontos de interesse e é proposta uma função de correspondência usando as diferenças nas magnitudes e direções dos gradientes de intensidade entre as imagens RGB e IR. Foram realizados vários experimentos com a técnica proposta, indicando que é possÃvel utilizar esta técnica obtendo-se erros residuais inferiores a 1,5 pixel
Articulated Whole-Body Atlases for Small Animal Image Analysis: Construction and Applications
Bone and mineral researc
How to measure the pose robustness of object views
The viewing hemisphere of a three-dimensional object can be partitioned into areas of similar views, which provide pose robustness. We compare two procedures for measuring the robustness of views to pose variation: tracking of object features, i.e. Gabor wavelet responses, by utilizing the continuity of successive views and matching of features in different views, which are assumed to be independent. Both procedures proved to be appropriate to detect canonical views. We found no difference concerning the size of the view bubbles, but tracking provides more precise correspondences than matching. Tracking is more appropriate for recognizing changes of features, whereas matching is more suitable if features of the same appearance are to be found. q 2002 Elsevier Science B.V. All rights reserved. Keywords: Three-dimensional object perception; Pose robustness; Matching/tracking object features; Canonical views 1. Subject of investigation Many models have been proposed for three-dimensional object perception. Besides volume-based object representations, which seem to be very economical but often require the interaction from a user to acquire them, as for example, described in Ref. [1], many computational models combine two-dimensional views into the equivalent of a three-dimensiona
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