0000000001104871

AUTHOR

Bastien Billiot

showing 14 related works from this author

Systèmes imageurs 3D pour des applications agricoles : caractérisation de cultures et phénotypage de racines

2016

The development of the concepts of precision agriculture and viticulture since the last three decades has shown the need to use first 2D image acquisition techniques and dedicated image processing. More and more needs concern now 3D images and information. The main ideas of this chapter is thus to present some innovations of the 3D tools and methods in the agronomic domain. This chapter will particularly focus on two main subjects such as the 3D characterization of crop using Shape from Focus or Structure from Motion techniques and the 3D use for root phenotyping using rhizotron system. Results presented show that 3D information allows to better characterize crucial crop morphometric parame…

[SDE] Environmental Sciences0106 biological sciences2. Zero hungerRoot (linguistics)Focus (computing)SHAPE FROM FOCUSComputer scienceMachine vision3D reconstructionImage processing04 agricultural and veterinary sciencesPHENOTYPAGE15. Life on land01 natural sciencesData scienceDomain (software engineering)Agricultural science[SDE]Environmental Sciences040103 agronomy & agriculture0401 agriculture forestry and fisheriesStructure from motionSTRUCTURE FROM MOTIONPrecision agriculture010606 plant biology & botany
researchProduct

3D image acquisition system based on shape from focus technique

2013

agent Agrosup Dijon de l'UMREcolDurGEAPSI; This paper describes the design of a 3D image acquisition system dedicated to natural complex scenes composed of randomly distributed objects with spatial discontinuities. In agronomic sciences, the 3D acquisition of natural scene is difficult due to the complex nature of the scenes. Our system is based on the Shape from Focus technique initially used in the microscopic domain. We propose to adapt this technique to the macroscopic domain and we detail the system as well as the image processing used to perform such technique. The Shape from Focus technique is a monocular and passive 3D acquisition method that resolves the occlusion problem affecting…

Engineering[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[SDV]Life Sciences [q-bio]ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONscenesImage processingagronomic scenes[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyClassification of discontinuitieslcsh:Chemical technologyBiochemistryArticleAnalytical ChemistryDomain (software engineering)shape from focusDepth map0202 electrical engineering electronic engineering information engineeringagronomiclcsh:TP1-1185Computer vision3D image acquisition system;shape from focus;focus measure;agronomic;scenesDepth of fieldElectrical and Electronic EngineeringInstrumentationComputingMethodologies_COMPUTERGRAPHICS3D image acquisition systemfocus measureMonocular[ SDV ] Life Sciences [q-bio]business.industry3D image acquisition system; shape from focus; focus measure; agronomic scenesScene statisticsDistributed object021001 nanoscience & nanotechnologyAtomic and Molecular Physics and Optics020201 artificial intelligence & image processingArtificial intelligence0210 nano-technologybusiness
researchProduct

Pattern image enhancement by extended depth of field

2014

International audience

[SPI.NANO] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics[ SPI.NANO ] Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
researchProduct

Pattern image enhancement by extended depth of field

2014

Abstract Most optical defect localization techniques such as dynamic laser stimulation or photon emission microscopy require a pattern image of the device to be taken. The main purpose is for device navigation, but it also enables the analyst to identify the location of the monitored activity by superimposing it onto the pattern image. The defect localization workflow usually starts at low or medium magnification. At these scales, several factors can lead to a lack of orthogonality of the sample with the optical axis of the system. Therefore, images can be locally out of focus and poorly resolved. In this paper, a method based on Depth of Field Extension is suggested to correct the pattern …

business.industryMagnificationImage processingCondensed Matter PhysicsLaserAtomic and Molecular Physics and OpticsSurfaces Coatings and FilmsElectronic Optical and Magnetic Materialslaw.inventionFocus stackingOptical axisOpticslawComputer visionDepth of fieldArtificial intelligenceElectrical and Electronic EngineeringSafety Risk Reliability and QualitybusinessFocus (optics)Infrared microscopyMathematicsMicroelectronics Reliability
researchProduct

Extraction and fusion of spectral parameters for face recognition

2011

This is the copy of journal's version originally published in Proc. SPIE 7877: http://spie.org/x10.xml?WT.svl=tn7. Reprinted with permission of SPIE. Many methods have been developed in image processing for face recognition, especially in recent years with the increase of biometric technologies. However, most of these techniques are used on grayscale images acquired in the visible range of the electromagnetic spectrum. The aims of our study are to improve existing tools and to develop new methods for face recognition. The techniques used take advantage of the different spectral ranges, the visible, optical infrared and thermal infrared, by either combining them or analyzing them separately …

Near Infrared[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingBiometrics[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingInfraredComputer scienceElectromagnetic spectrumFeature extractionImage processing02 engineering and technologyShort Wave Infrared[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingGrayscaleFacial recognition system[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringFeature descriptorComputer visionFace recognition[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industryNear-infrared spectroscopyVisibleFeature extraction020201 artificial intelligence & image processingArtificial intelligencefeature descriptorbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing:Mathematics and natural science: 400::Information and communication science: 420::Simulation visualization signal processing image processing: 429 [VDP]
researchProduct

L'utilisation de la proxi-détection 3D pour la caractérisation du blé

2012

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
researchProduct

Mesure de netteté basée sur les descripteurs généralisés de Fourier appliquée à la reconstruction 3D

2013

National audience

[SDV] Life Sciences [q-bio][SDE] Environmental Sciences[SDV]Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal BiologyComputingMilieux_MISCELLANEOUS
researchProduct

What do we expect from high throughput phenotyping ?

2018

prod ?EASPEGEAPSIGESTADINRAPPHD; What do we expect from high throughput phenotyping ?. Séminaire Chinese Academy of Agricultural Science

[SDV] Life Sciences [q-bio][SDV]Life Sciences [q-bio]
researchProduct

Système d'acquisition dédié à la reconstruction 3D de scènes agronomiques

2011

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
researchProduct

Differentiation of plant species with hyperspectral and deep learning technology

2018

International audience

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy[ SDV.SA.AGRO ] Life Sciences [q-bio]/Agricultural sciences/Agronomy[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ComputingMilieux_MISCELLANEOUS[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
researchProduct

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
researchProduct

Les défis méthodologiques du phénotypage Haut Débit - Expectations of plant high throughput phenotyping and associated tools and methods

2022

[SDV] Life Sciences [q-bio]
researchProduct

Conception d’un dispositif d’acquisition d’images agronomiques 3D en extérieur et développement des traitements associés pour la détection et la reco…

2013

Thèse de Doctorat Sciences pour l’Ingénieur et Microtechniques, Spécialité Instrumentation et Information de l’Image Agrosup ECOLDUR (2013); Dans le cadre de l’acquisition de l’information de profondeur de scènes texturées, un processus d’estimation de la profondeur basé sur la méthode de reconstruction 3D « Shape from Focus » est présenté dans ce manuscrit. Les deux étapes fondamentales de cette approche sont l’acquisition de la séquence d’images de la scène par sectionnement optique et l’évaluation de la netteté locale pour chaque pixel des images acquises. Deux systèmes d’acquisition de cette séquence d’images sont présentés ainsi que les traitements permettant d’exploiter celle-ci pour …

[SDV] Life Sciences [q-bio]shape from focusévaluation de robustesse[SDV]Life Sciences [q-bio]mesure de nettetéreconstruction 3Ddescripteurs généralisés de Fourier
researchProduct

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
researchProduct