Spectral Characterization of a Prototype SFA Camera for Joint Visible and NIR Acquisition

International audienceMultispectral acquisition improves machine vision since it permits capturing more information on object surface properties than color imaging. The concept of spectral filter arrays has been developed recently and allows multispectral single shot acquisition with a compact camera design. Due to filter manufacturing difficulties, there was, up to recently, no system available for a large span of spectrum, i.e., visible and Near Infra-Red acquisition. This article presents the achievement of a prototype of camera that captures seven visible and one near infra-red bands on the same sensor chip. A calibration is proposed to characterize the sensor, and images are captured. Data are provided as supplementary material for further analysis and simulations. This opens a new range of applications in security, robotics, automotive and medical fields

3D image acquisition system based on shape from focus technique

agent Agrosup Dijon de l'UMREcolDurGEAPSIThis 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 the multi-cameras systems. Indeed, this problem occurs frequently in natural complex scenes like agronomic scenes. The depth information is obtained by acting on optical parameters and mainly the depth of field. A focus measure is applied on a 2D image stack previously acquired by the system. When this focus measure is performed, we can create the depth map of the scene

Discrete wavelet transform based multispectral filter array demosaicking

International audienceThe idea of colour filter array may be adapted to multi-spectral image acquisition by integrating more filter types into the array, and developing associated demosaicking algorithms. Several methods employing discrete wavelet transform (DWT) have been proposed for CFA demosaicking. In this work, we put forward an extended use of DWT for mul-tispectral filter array demosaicking. The extension seemed straightforward, however we observed striking results. This work contributes to better understanding of the issue by demonstrating that spectral correlation and spatial resolution of the images exerts a crucial influence on the performance of DWT based demosaicking

Evaluation of the Colorimetric Performance of Single-Sensor Image Acquisition Systems Employing Colour and Multispectral Filter Array

International audienceSingle-sensor colour imaging systems mostly employ a colour filter array (CFA). This enables the acquisition of a colour image by a single sensor at one exposure at the cost of reduced spatial resolution. The idea of CFA fit itself well with multispectral purposes by incorporating more than three types of filters into the array which results in multispectral filter array (MSFA). In comparison with a CFA, an MSFA trades spatial resolution for spectral resolution. A simulation was performed to evaluate the colorimetric performance of such CFA/MSFA imaging systems and investigate the trade-off between spatial resolution and spectral resolution by comparing CFA and MSFA systems utilising various filter characteristics and demosaicking methods including intra-and inter-channel bilinear interpolation as well as discrete wavelet transformed based techniques. In general, 4-band and 8-band MSFAs provide better or comparable performance than the CFA setup in terms of CIEDE2000 and S-CIELAB colour difference. This indicates that MSFA would be favourable for colorimetric purposes

Conception d'un dispositif d'acquisition d'images agronomiques 3D en extérieur et développement des traitements associés pour la détection et la reconnaissance de plantes et de maladies

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 la suite du processus d'estimation de la profondeur. L'étape d'évaluation de la netteté des pixels passe par la comparaison des différents opérateurs de mesure de netteté. En plus des opérateurs usuels, deux nouveaux opérateurs basés sur les descripteurs généralisés de Fourier sont proposés. Une méthode nouvelle et originale de comparaison est développée et permet une analyse approfondie de la robustesse à différents paramètres des divers opérateurs. Afin de proposer une automatisation du processus de reconstruction, deux méthodes d'évaluation automatique de la netteté sont détaillées. Finalement, le processus complet de reconstruction est appliqué à des scènes agronomiques, mais également à une problématique du domaine de l'analyse de défaillances de circuits intégrés afin d'élargir les domaines d'utilisationIn the context of the acquisition of depth information for textured scenes, a depth estimation process based on a 3D reconstruction method called "shape from focus" is proposed in this thesis. The two crucial steps of this approach are the image sequence acquisition of the scene by optical sectioning and the local sharpness evaluation for each pixel of the acquired images. Two acquisition systems have been developed and are presented as well as different image processing techniques that enable the image exploitation for the depth estimation process. The pixel sharpness evaluation requires comparison of different focus measure operators in order to determine the most appropriate ones. In addition to the usual focus measure operators, two news operators based on generalized Fourier descriptors are presented. A new and original comparison method is developped and provides a further analysis of the robustness to various parameters of the focus measure operators. In order to provide an automatic version of the reconstruction process, two automatic sharpness evaluation methods are detailed. Finally, the whole reconstruction process is applied to agronomic scenes, but also to a problematic in failure analysis domain aiming to expand to other applicationsDIJON-BU Doc.électronique (212319901) / SudocSudocFranceF

High Dynamic Range Spectral Imaging Pipeline For Multispectral Filter Array Cameras

Spectral filter arrays imaging exhibits a strong similarity with color filter arrays. This permits us to embed this technology in practical vision systems with little adaptation of the existing solutions. In this communication, we define an imaging pipeline that permits high dynamic range (HDR)-spectral imaging, which is extended from color filter arrays. We propose an implementation of this pipeline on a prototype sensor and evaluate the quality of our implementation results on real data with objective metrics and visual examples. We demonstrate that we reduce noise, and, in particular we solve the problem of noise generated by the lack o

Energy balance in Spectral Filter Array camera design

Multispectral imaging permits to capture more spectral information on object surface properties than color imaging. This is useful for machine vision applications. Transmittance spectral filter arrays combined with a solid state sensor form an emerging technology used for snapshot acquisition. In spectral filter arrays technology, the sensitivities of the camera have critical consequences, not only on applications, but also in the viability of the system. We discuss how to balance the energy of each channel in single exposure multispectral imaging

Spectral Characterization of a Prototype SFA Camera for Joint Visible and NIR Acquisition

Multispectral acquisition improves machine vision since it permits capturing more information on object surface properties than color imaging. The concept of spectral filter arrays has been developed recently and allows multispectral single shot acquisition with a compact camera design. Due to filter manufacturing difficulties, there was, up to recently, no system available for a large span of spectrum, i.e., visible and Near Infra-Red acquisition. This article presents the achievement of a prototype of camera that captures seven visible and one near infra-red bands on the same sensor chip. A calibration is proposed to characterize the sensor, and images are captured. Data are provided as supplementary material for further analysis and simulations. This opens a new range of applications in security, robotics, automotive and medical fields

Evaluation de l’Effet des Eaux Usées Industrielles sur la Qualité de l’Eau de la Rivière Klou au Centre du Bénin

La présente étude a pour objectif d’évaluer l’impact des eaux usées industrielles sur la qualité de l’eau de la rivière Klou. Pour cela, des prélèvements d’eau ont été effectués avec une fréquence mensuelle sur des stations témoins et exposées. Les analyses physico-chimiques et le calcul de l’indice de Pollution Organique (IPO) ont été effectués. En période pluvieuse, les valeurs des paramètres physico-chimiques (pH, conductivité, TDS, ammonium, DBO5, nitrate, nitrite et orthophosphates) etaient faibles. De plus, les fortes valeurs des paramètres étudiés sont observées sur les stations plus exposées. Les résultats de l’analyse en composantes principales (ACP) sur les paramètres physico-chimiques ont révélé deux groupes  de stations. Le premier est constitué des deux stations témoins caractérisées par les faibles valeurs des paramètres étudiés alors que le second est composé des stations plus exposées et celles de l’aval avec les fortes valeurs des paramètres étudiés. L’indice de pollution organique a révélé une pollution modérée au niveau des stations témoins et une pollution organique forte et très forte respectivement au niveau des stations plus exposées et celles de l’aval. Il est nécessaire alors de mettre en place une politique de  restauration de la qualité écologique des eaux de cette rivière et des centres d’épuration opérationnels et efficaces.   The objective of this study was to assess the impact of industrial wastewater on the water quality of the Klou River. For this purpose, water sampling was conducted with a monthly frequency on control and exposed stations. Physico-chemical analyses and the calculation of the Organic Pollution Index (IPO) were carried out. In rainy periods, the values of the physico-chemical parameters (pH, conductivity, TDS, ammonium, BOD5, nitrate, nitrite and orthophosphates) were low. Moreover, the high values of the studied parameters were observed at the more exposed stations. The results of the principal component analysis (PCA) on the physico-chemical parameters revealed two groups of stations. The first consists of the two control stations characterized by low values of the studied parameters, while the second consists of the more exposed stations and those downstream with high values of the studied parameters. The organic pollution index revealed moderate pollution at the control stations and strong and very strong organic pollution respectively at the more exposed stations and those downstream. It is then necessary to put in place a mechanism to restore the ecological quality of the waters of this river and operational and effective purification centres

A method of using segmentation of color images and shape factors with frontier rates to identify onion and weeds in field

Dans cet article nous proposons une méthode pour résoudre le problème du recouvrement des feuilles d'oignons et des mauvaises herbes. Elle comporte trois étapes : Une segmentation des images en beaucoup de petit régions par la couleur; Une première fusion de ces petites régions à partir de l'étude des frontières et selon la couleur; Une seconde fusion suit une analyse de la forme des régions obtenues : si les petites régions peuvent reconstruire une forme de feuille d'oignon ou de feuille de mauvaises herbes, elles sont fusionnées , sinon elles ne le sont pas