Search results for "image processing"

showing 10 items of 3285 documents

Capteurs et images aériennes pour l’évaluation du peuplement de mauvaises herbes

2013

AIRINOV is specialized in use of UAV for precision agriculture. Thanks to a high spatial resolution up to 1.5 cm/pixel in RGB images, discrimination between vegetation (crop row, weed) and soil can be done. Variability can be detected in weed density inside the whole field. The detection of weeds in the inter-row of hoed row crops was tested on RGB images. The methodology developed is based on Hough transform, and is composed of three main steps: image segmentation, soil/vegetation discrimination and crop rows localization. First results are promising but need complementary measures for validation.

[SDE] Environmental Sciences[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingTransformée de Hough[SDV]Life Sciences [q-bio][ SDV.SA.STA ] Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agriculturedrone[SDV] Life Sciences [q-bio]images RGB THR[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[SDV.SA.STA]Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agriculture[SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biologyadventices
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Mesure de netteté basée sur les descripteurs généralisés de Fourier appliquée à la reconstruction 3D par Shape from Focus

2013

National audience; L'étape principale de la méthode de reconstruction 3D " Shape from Focus " est l'utilisation d'un opérateur de mesure de netteté de chaque pixel de la séquence d'image. Le choix de l'opérateur de mesure de netteté est une étape cruciale pour une reconstruction 3D de qualité. La précision de la mesure de netteté dépend de la taille du voisinage autour du pixel choisi et de la présence ou non de bruit additif dans la séquence d'images. Dans cet article, nous présentons deux nouveaux opérateurs de mesure de netteté basés sur les Descripteurs Généralisés de Fourier. Une nouvelle étude comparative des différents opérateurs est présentée. Cette comparaison est basée sur un plan…

[SDE] Environmental Sciences[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[SDV]Life Sciences [q-bio][ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing??[SDV] Life Sciences [q-bio]Mesure de netteté[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingDescripteurs généralisés de Fourier[SDE]Environmental SciencesShape from Focus[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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3D ACQUISITION SYSTEM APPLIED TO AGRONOMIC SCENES

2012

International audience; To improve results in automatic wheat ear counting by proxy-detection for early yield prediction, we need depth information of the scene. In this paper, we describe our 3D acquisition system dedicated to reconstruction of agronomic scenes. This system is composed of a camera mounted on a linear displacement driven by a microcontroller. The linear displacement allows acquiring a set of images in different distances to the scene. This image stack is used to apply shape from focus technique which is a passive and monocular 3D reconstruction method. This technique consists in the application of a focus measure for every pixel in the stack. An approximation method is used…

[SDE] Environmental Sciences[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[SDV]Life Sciences [q-bio][SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/AgronomyComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONagronomic scenes[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingcrop analysis[SDV] Life Sciences [q-bio][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ SDV.SA.AGRO ] Life Sciences [q-bio]/Agricultural sciences/Agronomyacquisition system[SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology3D reconstruction[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingComputingMethodologies_COMPUTERGRAPHICS
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Spray droplet characteristics measured using high speed imaging techniques

2016

Presented at Conference International Advances in Pesticide Application (IAPA), Barcelone, ESP (2016-01-13 - 2016-01-15).; International audience; Spray droplet characteristics are important features of an agricultural spray. The objective of this study is to measure the droplet size for different types of hydraulic spray nozzles using a developed backlighted image acquisition system and image processing technique. An in-focus droplet criterion was established to decide whether a droplet is in focus and can be measured in an accurate way. Tests included five different nozzles (Albuz ATR orange and red, TeeJet XR 110 01, XR 110 04 and Al 110 04).

[SDE] Environmental Sciences[SDV.SA]Life Sciences [q-bio]/Agricultural sciences[SDV.SA] Life Sciences [q-bio]/Agricultural sciences[SDV]Life Sciences [q-bio]droplet generatorspray characterisationdroplet size[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SDV] Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biologyhigh speed imaging[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[ SDV.SA ] Life Sciences [q-bio]/Agricultural sciences[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Estimation de l’indice foliaire et de la biomasse du blé et des adventices par imagerie visible et machine learning : vers un nouvel indicateur non d…

2019

National audience; Cette étude propose d’estimer précocement par imagerie deux variables clés dans la gestion des cultures et dans la compétition culture-adventices : l’indice foliaire (LAI) et la biomasse aérienne sèche (BM). Une expérimentation a été conduite au champ pendant la phase végétative d’une culture de blé. Pour chaque peuplement (culture de blé, adventices), les taux de couverture du sol par la végétation (TCc, TCw) ont été déduits du traitement d’image basé sur une technique de machine learning. LAI et BM ont été mesurés de façon destructive. Puis, une calibration a été réalisée entre TC et LAI d’une part et entre TC et BM d’autre part. Ce travail pourrait, à terme, faciliter …

[SDE] Environmental Sciencesnuisibilitéharmfulnessbiomass[SDV]Life Sciences [q-bio][SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/AgronomyAdventiceImagerie visibleimage visible[SDV] Life Sciences [q-bio]Indice foliairemachine learning[SDE]Environmental Sciencesbiomasse[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biologyadventicesvisible image[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingweed
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L’analyse spectrale de la lumière réfléchie permet de différencier les différentes étapes des lésions inflammatoires de la muqueuse gastrique dans un…

2015

International audience

[SDV.CAN] Life Sciences [q-bio]/Cancer[SDV.CAN]Life Sciences [q-bio]/Cancer[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing[ SDV.CAN ] Life Sciences [q-bio]/Cancer
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Toward the development of a remote photoplethysmographic sensor

2019

Heart-rate estimation performed with remote photoplethysmography is a very active research field. Since pioneer works in 2010, which demonstrated the feasibility of the measure with low-grade consumers’ camera (webcam), the number of scientific publications have increased significantly in the domain. Hence, we observe a multiplication of the methods in order to retrieve the photoplethysmographic signal which hasled to an increased precision and quality of the heartrate estimation. Region of interest segmentation is a key step of the processing pipeline in order to maximize the quality of the measured signal. We propose a new method to perform remote photoplethysmographic measurement using a…

[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/ImagingImage processing[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]Superpixels segmentation[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingTraitement d’imagesPhotopléthysmographie sans contactRemote photoplethysmographySegmentation en superpixels[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]Biomedical engineeringIngénierie biomédicale[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Improved estimation of the left ventricular ejection fraction using a combination of independent automated segmentation results in cardiovascular mag…

2014

—This work aimed at combining different segmenta-tion approaches to produce a robust and accurate segmentation result. Three to five segmentation results of the left ventricle were combined using the STAPLE algorithm and the reliability of the resulting segmentation was evaluated in comparison with the result of each individual segmentation method. This comparison was performed using a supervised approach based on a reference method. Then, we used an unsupervised statistical evaluation, the extended Regression Without Truth (eRWT) that ranks different methods according to their accuracy in estimating a specific biomarker in a population. The segmentation accuracy was evaluated by focusing o…

[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[ SDV.MHEP.CSC ] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing[SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system
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First steps toward the generation of PET/MR attenuation map in the case of prostate cancer

2015

Congrès sous l’égide de la Société Française de Génie Biologique et Médical (SFGBM).; National audience; A new methodology providing the first step towards the generation of attenuation maps for PET/MR systems based solely on MR information is presented in this paper. From T1-and T2-weighted MR data set and anatomical-based knowledge, our method segments and classifies the attenuation-differing regions of the patient's pelvis using a robust implementation of the weighted fuzzy C-means algorithm. Providing no signal, particular process is performed for the bones. We have demonstrated the feasibility of this approach by correctly segmenting and classifying six attenuation-differing regions on…

[SDV.IB] Life Sciences [q-bio]/BioengineeringImage Processing[SDV.IB]Life Sciences [q-bio]/Bioengineering[ SDV.IB ] Life Sciences [q-bio]/BioengineeringMagnetic Resonance Imaging
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Vers le développement d'un capteur photoplétysmographique sans contact

2019

Heart-rate estimation performed with remote photoplethysmography is a very active research field. Since pioneer works in 2010, which demonstrated the feasibility of the measure with low-grade consumers’ camera (webcam), the number of scientific publications have increased significantly in the domain. Hence, we observe a multiplication of the methods in order to retrieve the photoplethysmographic signal which has led to an increased precision and quality of the heart-rate estimation. Region of interest segmentation is a key step of the processing pipeline in order to maximize the quality of the measured signal. We propose a new method to perform remote photoplethysmographic measurement using…

[SDV.IB] Life Sciences [q-bio]/BioengineeringSans contacts[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]Embarqué[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Vital signs[SDV.IB]Life Sciences [q-bio]/BioengineeringContactlessEmbeded[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSignes vitaux[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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