Characterization of a calcium phospho-silicated apatite with iron oxide inclusions

An iron oxide containing calcium phosphate–silicate hydroxyapatite was synthesized by calcination at 900 °C of a sample obtained by precipitation in basic aqueous solution of Ca, P, Si, Fe and Mg containing acidic solution made from dissolution of natural minerals. XRD and FTIR were used for crystallographic characterization of the main apatitic phase. Its composition was determined using ICP-AES. EDX coupled with SEM and TEM evidenced the heterogeneity of this compound and the existence of iron–magnesium oxide. Magnetic analyses highlighted that this phase was non-stoichiometric magnesioferrite (Mg1.2Fe1.8O3.9) spherical nanoparticles. Those analyses also put into evidence the role of calcination in synthesis. Carbonates detected by FTIR and estimated by SEM-EDX in non-calcinated sample were removed from apatitic structure, and crystallization of apatite was enhanced during heating. Moreover, there was phase segregation that led to magnesioferrite formation

Estimates of fracture density and uncertainties from well data

International audienceThis paper aims at building a method to estimate the probability law governing the 3D fracture density of a fractured rock conditioned to the number of traces observed on a borehole image when the spatial distribution of fracture centers is assumed to follow a Poisson process. A closed-form expression of this law, allowing to calculate its mean value as well as a confidence interval, is derived in both cases of a lineic well (scanline) and a cylindrical well. The latter is better adapted to the situation of fracture size of the same order of magnitude as the well radius, which enables the presence of partial traces. In particular, the method takes into account the bias in the density estimate due to the fact that a fracture may cut the well along two distinct traces according to the considered fracture size. Monte Carlo simulations finally show a good agreement with the theoretical results of mean density and confidence interval

Iterative Search with Local Visual Features for Computer Assisted Plant Identification

To support computer assisted plant species identification in a realistic, uncontrolled picture-taking condition, we put forward an approach relying on local image features. It combines query by example and relevance feedback to support both the localization of potentially interesting image regions and the classification of these regions as representing or not the target species. We show that this approach is successful, and makes prior segmentation unnecessary

L'identification des adventices assistée par ordinateur avec le système IDAO

Identification of crop weeds is essential to get the information needed for elaborating efficient control methods. Non specialised people had difficulties to do this identification with classical tools, such as floras or field guides (too technical, unsuitable for seedlings or partial samples, process difficult to follow...). That brought us to develop a new system for plant recognition assisted by computer that was called IDAO (IDentification Assistée par Ordinateur). This software has the distinctive feature to use a graphical identification system by identikit. This identikit allows the user to build the image of the plant from traits freely chosen according to the specimen or to the user. It tolerates observation errors or polymorphism. Species are listed by their probability of similarity with the identikit. Descriptions, illustrations and information (biology, ecology, control...) are available at any time in local or online Html pages. These descriptive files can be regularly updated on the Web site. IDAO is a multilingual and multiplatform system. It can be used on PC (from cdrom or downloaded) or directly in the field on ultra mobile computer. Several applications have been published on weed floras of different cropping systems (rice, cotton, food crops, sugarcane...) and for different world areas (Africa, Asia, India, Indian Ocean), and also for other kinds of plants (trees, orchids...). The IDAO system will evolve during the Pl@ntnet project that will start in early 2009. IDAO will be available as free software on an Internet platform, for every body can develop by himself or under collaboration new applications available for all the user community. This identification system will be linked to an automatic recognition tool, using image analysis.L’identification des adventices d’une culture est une phase primordiale pour accéder à l’information nécessaire à l’élaboration de moyens de lutte performants. Les difficultés rencontrées par les non botanistes pour réaliser cette identification avec les outils classiques comme les flores ou les manuels (trop techniques, inefficaces pour les plantules ou les spécimens incomplets, processus difficile à suivre…) nous ont amené à développer un nouveau système de reconnaissance assistée par ordinateur appelé IDAO (IDentification Assistée par Ordinateur). Ce logiciel a la particularité d’utiliser un système d’identification graphique par portrait robot qui permet à l’utilisateur de construire l’image de la plante à partir de caractères choisis librement en fonction du spécimen ou de l’utilisateur et de tolérer les erreurs d’observation ou le polymorphisme. Les espèces sont listées en permanence en fonction de leur similitude avec ce portrait robot. Descriptions, illustrations et informations (biologie, écologie, lutte…) sont accessibles à tout moment sous la forme de pages au format Html disponibles localement ou sur un site Internet, et donc régulièrement actualisables. IDAO est multilingue et multiplateformes informatique. Il peut être utilisé sur PC (installable à partir de cdrom ou téléchargeable) ou directement au champ sur ordinateur ultra mobile. Une série d’applications a déjà été développée pour des flores de différents systèmes de cultures (riz, cotonnier, vivrier, canne à sucre…) et de différentes régions du monde (Afrique, Inde, Asie, Océan Indien) ainsi que pour d’autres types de plantes (arbres, orchidées…). Le système IDAO va évoluer dans le cadre du projet Pl@ntnet qui démarrera début 2009. Il sera mis à disposition sous forme de logiciel libre sur une plateforme Internet permettant ainsi à tout utilisateur de développer seul ou en partenariat une application et de la mettre à disposition de la communauté d’utilisateurs. Ce système d’identification sera associé à un outil de reconnaissance automatique par analyse d’images

The ImageCLEF 2012 Plant Identification Task

International audienceThe ImageCLEF's plant identification task provides a testbed for the system-oriented evaluation of plant identification, more precisely on the 126 tree species identification based on leaf images. Three types of image content are considered: Scan, Scan-like (leaf photographs with a white uniform background), and Photograph (unconstrained leaf with natural background). The main originality of this data is that it was specifically built through a citizen sciences initiative conducted by Tela Botanica, a French social network of amateur and expert botanists. This makes the task closer to the conditions of a real-world application. This overview presents more precisely the resources and assessments of task, summarizes the retrieval approaches employed by the participating groups, and provides an analysis of the main evaluation results. With a total of eleven groups from eight countries and with a total of 30 runs submitted, involving distinct and original methods, this second year pilot task confirms Image Retrieval community interest for biodiversity and botany, and highlights further challenging studies in plant identification

The ImageCLEF 2013 Plant Identification Task

International audienceThe ImageCLEF's plant identification task provides a testbed for a system-oriented evaluation of plant identification about 250 species trees and herbaceous plants based on detailed views of leaves, flowers, fruits, stems and bark or some entire views of the plants. Two types of image content are considered: SheetAsBackgroud which contains only leaves in a front of a generally white uniform background, and NaturalBackground which contains the 5 kinds of detailed views with unconstrained conditions, directly photographed on the plant. The main originality of this data is that it was specifically built through a citizen sciences initiative conducted by Tela Botanica, a French social network of amateur and expert botanists. This makes the task closer to the conditions of a real-world application. This overview presents more precisely the resources and assessments of task, summarizes the retrieval approaches employed by the participating groups, and provides an analysis of the main evaluation results. With a total of twelve groups from nine countries and with a total of thirty three runs submitted, involving distinct and original methods, this third year task confirms Image Retrieval community interest for biodiversity and botany, and highlights further challenging studies in plant identification