Results 241 to 250 of about 11,974,913 (292)

Image Alignment

2006
Besides stating the problem of image registration this chapter is built on the following parts : 1) Similarity estimation by level sets. We use the Fast Level Sets Transform (see the chapter on TV minimization) to extract reliable features from both images. To each feature we associate similarity invariants, then we consider pairs of features (F1, F2),
Dibos, Françoise, Koepfler, Georges, Monasse, Pascal   +2 more
openaire   +3 more sources

On the extraction and alignment of image edges

Spatial Vision, 1986
In this paper the types of image filtering, segmentation and correlational processes which are consistent with the ability of human observers to align edges in arbitrary two-dimensional images are considered. Edge-only versions of a number of images were computed by pre-filtering, segmenting and using laplacians to extract luminance boundaries.
T, Caelli, J, Yuzyk
openaire   +2 more sources

Efficient alignment of fingerprint images

Object recognition supported by user interaction for service robots, 2003
Fingerprint matching is a common technique for biometric authentication. Solid state sensors for fingerprint recognition are used in small sized embedded systems. The size of these sensors makes it necessary to store several impressions of the same finger.
Herbert Ramoser, B. Wachmann, Horst Bischof   +2 more
openaire   +2 more sources

Aligning images with multiple objectives

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), 2008
Most high level interpretation tasks in image analysis rely on image registration (alignment) process. Basically, image registration consists in finding the geometric transformation that best aligns two or several images. In this paper, we focus on mono-modality image alignment. The core task to do in this case is to put into correspondence two sets of
Souham Meshoul, Mohamed Batouche
openaire   +2 more sources

Radiometric alignment of image sequences

Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., 2004
Color values in an image are related to image irradiance by a nonlinear function called radiometric response function. Since this function depends on the aperture and the shutter speed, image intensity of a same object may vary during the acquisition of an image sequence due to auto exposure feature of the camera.
Seon Joo Kim, Marc Pollefeys
openaire   +2 more sources

Lighting Alignment for Image Sequences

2015
Lighting is one of the challenges for image processing. Even though some algorithms are proposed to deal with the lighting variation for images, most of them are designed for a single image but not for image sequences. In fact, the correlation between frames can provide useful information to remove the illumination diversity, which is not available for
Xiaoyue Jiang, Xiaoyi Feng, Jun Wu, Jinye Peng   +3 more
openaire   +2 more sources

Multisensor alignment of image manifolds

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, 2013
The access to many sources of satellite information is nowadays a reality. However, few methods allow to consider simultaneously data coming from different sensors, due to the differences in numbers of bands, spatial resolution and changes in the acquisition conditions.
Devis Tuia, Maxime Trolliet, Michele Volpi   +2 more
openaire   +1 more source

Imaging and Alignment for Image-Guided Radiation Therapy

Journal of Clinical Oncology, 2007
Image-guided radiation therapy is an exciting new area that focuses heavily on the potential benefit of advanced imaging and image registration to improve precision, thus limiting morbidity and potentially allowing for safe delivery of increased dose.
James M, Balter, Marc L, Kessler
openaire   +2 more sources

Image alignment for 3D reconstruction in a SEM

Microelectronics Reliability, 2005
In a previous paper [1] a procedure to extract the third dimension from back-scattered electron has been proposed. The 3D recovery process involves the acquisition of four images and the computation of surface gradients; thus, a specific algorithm finds the depth map of the given surface.
Pintus R, PODDA, SIMONA, VANZI, MASSIMO
openaire   +3 more sources

Field‐aligned Quadrangulation for Image Vectorization

Computer Graphics Forum, 2019
AbstractImage vectorization is an important yet challenging problem, especially when the input image has rich content. In this paper, we develop a novel method for automatically vectorizing natural images with feature‐aligned quad‐dominant meshes. Inspired by the quadrangulation methods in 3D geometry processing, we propose a new directional field ...
Guangshun Wei, Yuanfeng Zhou, Xifeng Gao, Qian Ma, Shiqing Xin, Ying He 0001   +5 more
openaire   +3 more sources