Search results for "image processing"
showing 10 items of 3285 documents
Application of Genetic Algorithms to 3-D Shape Reconstruction in an Active Stereo Vision System
2001
In this paper, a new method for reconstructing 3-D shapes is proposed. It is based on an active stereo vision system composed of a camera and a light system which projects a set of structured laser rays on the scence to be analyzed. The depth information is provided by matching the laser rays and the corresponding spots appearing in the image. The matching task is performed by using Genetic Algorithms (GAs). The process converges towards the optimum solution which proves that GAs can effectively be used for this problem. An efficient 3-D reconstruction method is introduced. The experimental results demonstrate that the proposed approach is stable and provides high accuracy 3-D object recons…
A new minimum spanning tree-based method for shape description and matching working in Discrete Cosine space
2009
In this article, a new minimum spanning tree-based method for shape description and matching is proposed. Its properties are checked through the problem of graphical symbols recognition. Recognition invariance in front shift and multi-oriented noisy objects was studied in the context of small and low resolution binary images. The approach seems to have many desirable properties, even if the construction of graphs induces an expensive algorithmic cost. In order to reduce time computing, an alternative solution based on image compression concepts is provided. The recognition is realized in a compact space, namely the Discrete Cosine space. The use of block discrete cosine transform is discuss…
Real Time Stereo Matching Using Two Step Zero-Mean SAD and Dynamic Programing
2018
Dense depth map extraction is a dynamic research field in a computer vision that tries to recover three-dimensional information from a stereo image pair. A large variety of algorithms has been developed. The local methods based on block matching that are prevalent due to the linear computational complexity and easy implementation. This local cost is used on global methods as graph cut and dynamic programming in order to reduce sensitivity to local to occlusion and uniform texture. This paper proposes a new method for matching images based on a two-stage of block matching as local cost function and dynamic programming as energy optimization approach. In our work introduce the two stage of th…
Which Is Which? Evaluation of Local Descriptors for Image Matching in Real-World Scenarios
2019
Matching with local image descriptors is a fundamental task in many computer vision applications. This paper describes the WISW contest held within the framework of the CAIP 2019 conference, aimed at benchmarking recent descriptors in challenging planar and non-planar real image matching scenarios. According to the contest results, the descriptors submitted to the competition, most of which based on deep learning, perform significantly better than the current state-of-the-art in image matching. Nonetheless, there is still room for improvement, especially in the case of non-planar scenes.
Stereo Matching Tecniques for Cloud-top Height Retrieval
2006
This paper presents an ongoing study for the estimation of the cloud-top height by using only geometrical methods. It is based on the hypothesis that an infra-red camera is on board a satellite and pairs of images concern nearly the same scene. Stereo-vision techniques are therefore explored in order to test the methodology for height retrieval and in particular results of several techniques of stereo matching are evaluated. This study includes area-based matching algorithms by implementing the basic versions, without considering any further steps of optimisation to improve the results. Dense depth maps are the final outputs whose reliability is verified by computing error statistics with r…
Customer recommendation based on profile matching and customized campaigns in on-line social networks
2019
We propose a general framework for the recommendation of possible customers (users) to advertisers (e.g., brands) based on the comparison between On-Line Social Network profiles. In particular, we associate suitable categories and subcategories to both user and brand profiles in the considered On-line Social Network. When categories involve posts and comments, the comparison is based on word embedding, and this allows to take into account the similarity between the topics of particular interest for a brand and the user preferences. Furthermore, user personal information, such as age, job or genre, are used for targeting specific advertising campaigns. Results on real Facebook dataset show t…
Physics-Aware Gaussian Processes for Earth Observation
2017
Earth observation from satellite sensory data pose challenging problems, where machine learning is currently a key player. In recent years, Gaussian Process (GP) regression and other kernel methods have excelled in biophysical parameter estimation tasks from space. GP regression is based on solid Bayesian statistics, and generally yield efficient and accurate parameter estimates. However, GPs are typically used for inverse modeling based on concurrent observations and in situ measurements only. Very often a forward model encoding the well-understood physical relations is available though. In this work, we review three GP models that respect and learn the physics of the underlying processes …
A stochastic shape and orientation model for fibres with an application to carbon nanotubes
2012
Methods are introduced for analysing the shape and orientation of planar fibres from greyscale images of fibrous systems. The sequence of image processing techniques needed for segmentation of fibres is described. The identified fibres were interpreted as deformed line segments for which two shape and two orientation parameters are estimated by the maximum likelihood method. The methods introduced are shown to perform quite well for simulated systems of deformed line segments with known properties. They were applied to TEM images of carbon nanotubes embedded in polycarbonate.
Determination of Bubble Size Distribution Using Ultrasound Array Imaging
2020
In this article, ultrasonic phased arrays are deployed as an imaging tool for industrial process analysis. Such arrays are typically used for sonar, medical diagnosis, and nondestructive testing; however, they have not yet been applied to industrial process analysis. The precise positioning of array elements and high frequencies possible with this technology mean that highly focused images can be generated, which cannot currently be achieved using ultrasound tomography. This article aims to highlight the potential of this technology for the measurement of bubble size distribution (BSD) and to demonstrate its application to both intrusive and noninvasive process measurements. Ultrasound imag…
Software-supported image quantification of angiogenesis in an in vitro culture system: application to studies of biocompatibility
2002
Healing of soft tissue trauma and bone discontinuities following implantation involves acute inflammatory reactions and the formation of blood vessels (angiogenesis). During angiogenesis new capillary vessels arise from the existing vasculature. Endothelial cells (EC) are the major cell type involved in angiogenesis. Corrosion of orthopaedic metallic implant materials (e.g. CoCr alloys) can cause locally high concentrations of heavy metal ions in the peri-implant tissues. Some divalent metal ions (Co2+, Ni2+, Zn2+) lead to the activation of EC in vitro. Upon exposure to these ions. EC release cytokines and chemokines and increase the expression of cell surface adhesion molecules, which repr…