Search results for "feature"
showing 10 items of 4091 documents
Learning the relevant image features with multiple kernels
2009
This paper proposes to learn the relevant features of remote sensing images for automatic spatio-spectral classification with the automatic optimization of multiple kernels. The method consists of building dedicated kernels for different sets of bands, contextual or textural features. The optimal linear combination of kernels is optimized through gradient descent on the support vector machine (SVM) objective function. Since a na¨ive implementation is computationally demanding, we propose an efficient model selection procedure based on kernel alignment. The result is a weight — learned from the data — for each kernel where both relevant and meaningless image features emerge after training. E…
Multimodal biometric recognition systems using deep learning based on the finger vein and finger knuckle print fusion
2020
Recognition systems using multimodal biometrics attracts attention because they improve recognition efficiency and high-security level compared to the unimodal biometrics system. In this study, the authors present a secure multimodal biometrics recognition system based on the deep learning method that uses convolutional neural networks (CNNs). The authors propose two multimodal architectures using the finger knuckle print (FKP) and the finger vein (FV) biometrics with different levels of fusion: the features level fusion and scores level fusion. The features extraction for FKP and FV are performed using transfer learning CNN architectures: AlexNet, VGG16, and ResNet50. The key step aims to …
Recent advances in remote sensing image processing
2009
Remote sensing image processing is nowadays a mature research area. The techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics, and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation…
Atlas selection strategy using least angle regression in multi-atlas segmentation propagation
2011
International audience; In multi-atlas based segmentation propagation, segmentations from multiple atlases are propagated to the target image and combined to produce the segmentation result. Local weighted voting (LWV) method is a classifier fusion method which combines the propagated atlases weighted by local image similarity. We demonstrate that the segmentation accuracy using LWV improves as the number of atlases increases. Under this context, we show that introducing diversity in addition to image similarity by using least-angle regression (LAR) criteria is a more efficient way to rank and select atlases. The accuracy of multi-atlas segmentation converges faster when the atlases are sel…
Small Sample Biometric Recognition Based on Palmprint and Face Fusion
2009
Contactless biometrics provide high comfort and hygiene in person recognition. Because of this, such systems are better accepted by the general public. This paper proposes an adaptive, contactless, biometric system which combines two modalities: palmprint and face. The processing chain has been designed to overcome embedded system constraints and small sample set problem: after a palmprint is extracted from a hand image, Gabor filters are applied to both the palmprint and face in order to extract parameters, which are then used for classification. Fusion possibilities are also discussed and tested using a multimodal database of 130 people designed by the authors. High recognition performanc…
<title>Achieving high performances at lower cost for real-time image rotation by using dynamic reconfiguration</title>
2001
FPGA components are widely used today to perform various algorithms (digital filtering) in real time. The emergence of Dynamically Reconfigurable (DR) FPGAs made it possible to reduce the number of necessary resources to carry out an image processing application (tasks chain). We present in this article an image processing application (image rotation) that exploits the FPGA's dynamic reconfiguration feature. A comparison is undertaken between the dynamic and static reconfiguration by using two criteria, cost and performance criteria. For the sake of testing the validity of our approach in terms of Algorithm and Architecture Adequacy , we realized an AT40K40 based board ARDOISE.
Image Segmentation by Deep Community Detection Approach
2017
International audience; To address the problem of segmenting an image into homogeneous communities this paper proposes an efficient algorithm to detect deep communities in the image by maximizing at each stage a new centrality measure, called the local Fiedler vector centrality (LFVC). This measure is associated with the sensitivity of algebraic connectivity to node removals. We show that a greedy node removal strategy, based on iterative maximization of LFVC, has bounded performance loss relative to the optimal, but intractable, combinatorial batch removal strategy. A remarkable feature of this method is the ability to segments the image automatically into homogeneous regions by maximizing…
Building Worlds Together with Sound and Music : Imagination as an Active Engagement between Ourselves
2019
By conforming to the enactive approach to human cognition, and by adopting the Tia DeNora’s concept of human–music interaction as an “in-action” perspective, Kai Tuuri and Henna-Riikka Peltola explore socially extended imagining with sounds and music. This is done through a question of how “shared places” of imagining with sound are established and maintained. Defining the activity of imagining as an essentially dynamic and generative process that takes place in a social reality, the authors propose that the processes of imagining are not only individual but also become exhibited and jointly engaged in social dialogues as well. By first discussing the theoretical foundations of this shared …
In situ Laser Induced Breakdown Spectroscopy as a tool to discriminate volcanic rocks and magmatic series, Iceland.
2015
7 pages; International audience; This study evaluates the potentialities of a lab-made pLIBS (portable Laser-Induced Breakdown Spectroscopy) to sort volcanic rocks belonging to various magmatic series. An in-situ chemical analysis of 19 atomic lines, including Al, Ba, Ca, Cr, Cu, Fe, Mg, Mn, Na, Si, Sr and Ti, from 21 sampled rocks was performed during a field exploration in Iceland. Iceland was chosen both for the various typologies of volcanic rocks and the rugged conditions in the field in order to test the sturdiness of the pLIPS. Elemental compositions were also measured using laboratory ICP-AES measurements on the same samples. Based on these latter results, which can be used to ident…
Preparation and evaluation of lauryl methacrylate monoliths with embedded silver nanoparticles for capillary electrochromatography
2012
In this article, capillary columns constituted by lauryl methacrylate monoliths with embedded silver nanoparticles (AgNPs) were developed and tested. Two incorporation approaches of AgNPs in monoliths were explored. The AgNPs were either photogenerated in situ during polymerization of the monolith by UV irradiation, or incorporated to the polymerization mixture (ex situ). The influence of the AgNP concentration on the morphological and chromatographic properties of the polymer matrix was investigated, and both the in situ and ex situ approaches were comparatively discussed. The morphology of the monoliths was characterized by electron microscopic techniques, and their electrochromatographic…