EP0818766B1 - Procédé de détection automatique de feux, notamment de feux de forêts - Google Patents
Procédé de détection automatique de feux, notamment de feux de forêts Download PDFInfo
- Publication number
- EP0818766B1 EP0818766B1 EP19970420115 EP97420115A EP0818766B1 EP 0818766 B1 EP0818766 B1 EP 0818766B1 EP 19970420115 EP19970420115 EP 19970420115 EP 97420115 A EP97420115 A EP 97420115A EP 0818766 B1 EP0818766 B1 EP 0818766B1
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- detection
- smoke
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- temporal
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- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Lifetime
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- 238000001514 detection method Methods 0.000 title claims description 59
- 238000000034 method Methods 0.000 title claims description 58
- 239000000779 smoke Substances 0.000 claims description 62
- 230000008569 process Effects 0.000 claims description 37
- 230000002123 temporal effect Effects 0.000 claims description 12
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- 238000001429 visible spectrum Methods 0.000 claims description 5
- 238000012544 monitoring process Methods 0.000 claims description 3
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Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/005—Fire alarms; Alarms responsive to explosion for forest fires, e.g. detecting fires spread over a large or outdoors area
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/12—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions
- G08B17/125—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions by using a video camera to detect fire or smoke
Definitions
- the invention defined in the following claims relates to a detection method automatic fire, including forest fire, based on the recognition of smoke from at least one a video camera, in particular of the CCD type, operating in the visible spectrum. This process makes it possible to detect at faster a fire start, even of limited extent (by example less than 4 m2), that it is directly visible or masked by the relief and this day and night.
- Forest fire detection is part of integral to fire fighting. Indeed, early warning of a fire allows limit the importance of the means to be used to control these fires.
- smoke detection based on the recognition of scroll movement has the disadvantage of require a system with very high spatial resolution, therefore great computing power.
- the motion detection of the curls of distant smoke covered by a few pixels, for example 2 x 2 or 3 x 3 is almost impossible to differentiate from a phenomenon fixed room such as the movement of a tree, or a group of people, or any other activity.
- this kind of process often call for the storage of a smoke-free reference image: the motion detection is obtained by subtracting from the reference image with the current image to set evidence the movements of the zones. faces multiple problems and especially those generated by continual variations in illumination caused by cloudy periods.
- this process does not allow the detection of complex smoke clouds: the effects conjugates of diffusion of matter in space, of a locally maintained hearth and finally winds, generate a complex phenomenon that makes any characterization of smoke by movement extraction. For example, a relatively calm start of fire does not produce any apparent movement. However, by strong wind, the scrolls produced often have unstable, multiple movements and very difficult identifiable.
- This document describes a process for automatic detection of fires, based on the recognition of smoke from at least minus a video camera, which involves taking a processing of still images obtained by the camera (s) in the visible spectrum, to detect and locate a possible smoke source, according to the preamble to the claim 1.
- This document is however limited to the fire detection in tunnels, and the process involved described is suitable for this application only, and not for a detection in an open environment.
- the process described in this document is sensitive to smoke filling a tunnel, but it cannot detect volutes or clearances of mobile and localized smoke.
- the present invention aims to avoid all of these disadvantages, and it thus proposes a process which is remarkable in particular by the fact that it makes it possible to detect a possible hearth of smoke still thin, for a early detection, and that it is able to differentiate the smoke from any other local phenomenon.
- the method consists in searching for in the images a small area of pixels with particularly chaotic variations in gray levels, by means of measuring spatiotemporal chaoticity index different pixel areas in the image.
- the method of the invention differs from methods based on the detection of any movement by the fact that it is based on the analysis of complexity spatio-temporal of almost immobile objects producing local grayscale variations.
- any object producing variations in gray levels can be analyzed simply as a movement of material is rejected by the process as a parasite.
- the principle of the process of the invention consists in recognize smoke as an inducing phenomenon in a specific area of the landscape a noise or chaos very important in space and time, unlike all other local phenomena.
- Spatio-temporal chaos results in the fact that smoke introduces into the pixel area it covers temporal variations in gray levels which are almost as diverse as those produced by a random noise, but which differ from such noise because they are characteristic of a dynamic object fractal.
- the fractal structure of an object is generally known to be purely spatial in nature, or purely temporal, but it can also be spatio-temporal, and its highlighting allows the differentiate from that of a noise or on the contrary from that of of an organized phenomenon.
- Spatio-temporal chaos indeed generates generally a wide range of time frequencies close to those induced by a Brownian movement, of which the time spectrum is that of white noise. Unlike purely electronic noise, this noise is characterized by the fact that it contains more bass frequencies. In the case of smoke, the low frequencies of the order of 0.1 Hz are even more marked.
- the method consists in carrying out a processing on sequences of still images of a landscape (obtained by CCD camera in the visible spectrum) for identify and locate a possible source of smoke, characterized by recognition at first a small area of pixels with variations grayscale temporal particularly low frequency, followed by analysis of this area to verify the presence of noise, decorrelation and high chaoticity.
- the primary advantage of this process is that it allows both the detection of thin smoke and thick smoke since thin smoke will be initially retained not thanks to the intensity of their gray level variations but thanks to the fact that they generate low frequencies.
- the process allows the detection of little smoke thick since they are detected by the fact that they generate particularly decorrelation indices high variations in pixel grayscale covered by smoke.
- the condition of low mobility of the object to detecting makes it possible to deal with smoke as well close as in the case of distant smoke, to the extent where this mobility is quantified in relation to size of the object and not according to the information of movement contained within the area it covers.
- the method makes it possible to detect sources of tiny fumes that cover only a very limited number pixels (4 pixels for example), because it analyzes basically the time structure of the levels of gray and little purely spatial information.
- the process is robust under the multiple conditions of detection, such as wind speed, orientation of the sensor, meteorology, the peculiarities of the landscape, the masking of the home by different obstacles, etc., since this process involves quantifying the complexity of the object and not to seek on the contrary a more or less defined spatio-temporal structure, such as its shape, speed, color, etc.
- the method makes it possible to characterize the smoke in that that it produces an effect which is not induced exclusively by movements of matter, and that is therefore unique or rare because variations in gray levels of all the pixels in an image are in the majority of cases produced by any movements of objects in the landscape at variable distance.
- the process according to the invention makes it possible to reject these zones thanks to the too low result of the calculation of their indices of correlation.
- the process uses a buffer which can permanently contain at least the Last 16 images.
- the system calculates a linear combination appropriate absolute values of all differences grayscale of the same pixel taken at instants different.
- the method uses values absolute instead of signed values in order to quantify the temporal evolution of each pixel whatever the nature of the background of the landscape on which the smoke is written, so as to attenuate the influence of the brightness of the background.
- the system calculates the new transformation, for a new step of time (corresponding to a new image acquisition), using the result of the previous calculation, and in it applying the appropriate changes.
- the system uses the assumption that the envelope smoke is very weakly mobile. This allows to eliminate possible portions of the "smoke" object which would come off the main envelope.
- This technique allows you to locate more precisely the focus of smoke which is defined as the lowest point of the envelope.
- the last step in the process is to perform a digital analysis of each object using all the space-time information of its pixels which on the one hand is stored in the global buffer (which contains the last 16 images at least), on the other hand in a selective buffer reserved for objects so to memorize their more distant past.
- This step consists of implementing more advanced algorithms relating to said information spatiotemporal. This calculation is allowed in practice, despite the complexity of these algorithms, thanks to the enormous compression of information from previous steps.
- the degree of disorder is quantified using noise calculations space-time of the object, while the degree of chaoticity is quantified using calculations which provide a measure of the sensitivity rate of the evolution of the object according to small differences in the repetitive grayscale of all of its pixels at different times.
- Spatio-temporal noise measurement is broken down measuring the rate of spatial decorrelation of variations grayscale, and in analysis of the distribution of differences in gray levels of pairs of pixels, which must strive for Gaussian law according to law normal.
- the detection criterion thus exploits the measurement noise and / or chaos measurement preferentially one in relation to the other according to the different detection conditions.
- the combination of the two measures generates a certain degree of redundancy because a pure space-time noise is at least as complex as smoke.
- the combination of these two measures is made necessary due to possible confusion between noise broad spectrum and smoke.
- the criterion based on the measurement of chaos is better but much more difficult to be implemented under certain conditions is why it should be relayed by the criterion based on the measurement of noise and more particularly of decorrelations between pixels.
- the imprecision of the measurement of degree of chaoticity of a space-time object is more large in cases where the number of pixels is insufficient, or excessive electronic noise. This difficulty is offset by the more important to the measurement of space-time noise which is easier to calculate.
- the measurement of the degree of chaoticity when practicable in preferential cases where the number of pixels is sufficient and the electronic noise fairly weak, allows to characterize more precisely the presence of smoke, because it is then more easily discernible from a phenomenon essentially producing noise, as can happen in the case of system placed under detection conditions particularly difficult.
- the invention makes it possible to detect very quickly, in a time notably between 10 and 40 seconds, smoke produced by a start of fire with very high reliability. She thus helps valuable and essential for operators responsible for surveillance of critical areas.
- the latter includes at least one local detection device, located on an area to be monitored or on the outskirts thereof, and comprising at least one fixed video camera connected to an autonomous processing unit, which analyzes the image of the camera according to the methods explained above.
- One or more detection devices are connected to a central unit, located remotely.
- This last equipped with visualization means for a human operator, serves as a checkpoint and command, but an important feature is the fact that the actual smoke detection done locally, not in the unit Central.
- the control and command is provided for viewing a sequence images of the part of the landscape around a hearth detected, said sequence being displayed at a rate strongly accelerated compared to its real rate acquisition, which facilitates visual interpretation gross profit obtained by the process of detection
- Figure 2 symbolically indicates an extent to monitor 1, supposedly rectangular, on which and at the periphery of which are installed detection 2, suitably distributed.
- Each detection device 2 shown on the Figure 3 includes one to three fixed CCD video cameras 4, installed in the same observation site and connected to an autonomous processing unit 5, powered by a energy source 6 and connected to a transmission 7, generally wireless, of low speed, in order to transmit alarm information remotely, device status information, photos, etc.
- Processing unit 5 capable of taking instructs the surveillance of an area without any intervention human, receives video images from cameras 4 which each scan a very large area (from 500 meters to 10 kilometers for an angle of 60 degrees per camera). Typically the observation surface of each camera 4 is 30 km2, for a total area of 90 km2 for a device 2 equipped with three cameras 4, such as mounted in Figure 3.
- meteorological sensors 8 can detect wind direction and speed, humidity, temperature, etc. are also connected to processing unit 5, in order to have information local weather.
- the preferred mode of establishment consists of placing the detection devices 2 on the area to be monitored 1 so as to cover several times each part of this range. This is desirable to solve the problems posed by "blinded" detectors (front sun, fog, ...), faulty detectors, etc.
- Complementary detectors 9 oriented differently from the previous ones, allowing to calculate with high accuracy the position of the detected lights, by a principle of triangulation.
- a central unit 10 which can also be designated as a control and command post, and common to a relatively high number of detection devices 2 monitoring a range 1 possibly very large, is connected to all these detection devices 2 by a network transmission 11, in particular hertzian, like the symbolizes FIG. 4.
- the central unit 10 comprises a control station 12 with screen, can be connected in particular to a screen managing display 13, to a printer 14, or any other peripheral equipment.
- the central unit 10 can thus receive the information and photos from all devices local detection 2, each of these devices realizing smoke detection, for the partial extent it monitors, implementing the process summarized by the flowchart of Figure 5, and using for this purpose two memories 15 and 16, designated respectively as “image memory” and "object memory”.
- the central unit 10 is thus informed in permanence of the status of each detection device 2. An image of the landscape seen by each detector will be available and refreshed in the shortest time possible and depending on the number of detectors sharing the same communication medium.
- the central unit 10 is equipped with a display suitable for managing multiple alarms the following way:
- This visualization method is very advantageous because it provides all the information necessary for the interpretation of multiple alarms to using the same display screen. She is original at least insofar as it uses a method of original film viewing. This method is powerful because it allows to automatically view IGN or polar coordinates and the actual location of the detected focus, by intersection of the half-lines which cut this hearth.
- the method of the invention can, if necessary, be implemented by inhibiting certain points predefined images, which correspond to homes permanent, for example a factory chimney.
- An advantageous consequence of the process is to provide an operator human, placed at the control and command post, the possibility to visually control the event which has caused detection.
- This visual check allows a the operator to check using a sequence of images the part of the landscape, located around the detected focus, that the phenomenon detected is smoke characteristic of a fire and estimate the severity of the event.
- the particularity of this sequence of images is to be viewed at a very accelerated pace like illustrated by figure 6. Accelerated viewing results from the selection, from the actual film 17 presenting a sequence of images, of certain images such as the 1st, the 11th, the 21st, the 31st, etc ..., to constitute an "accelerated" film 18.
- This process exploits the property that viewing at a very accelerated rate (of the order 25 to 50 frames per second) of a sequence of images smoke, improves recognition of smoke even when the spatial resolution is very low.
- One of the benefits of accelerated viewing is to compensate for the disadvantage of viewing rate too low, such as that of acquisition by example, which makes the observer lose the notion of the smoke dynamics.
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- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biodiversity & Conservation Biology (AREA)
- Fire-Detection Mechanisms (AREA)
Description
- la surveillance des zones à risque par des vigies: elle demande un grand nombre d'opérateurs qui sont d'effectifs non disponibles pour la lutte sur le front;
- le survol de ces zones par des moyens aériens : l'utilisation des moyens aériens (avions, hélicoptères) est très coûteuse, de plus, son efficacité n'est pas très intéressante. En effet, le survol consiste à parcourir un itinéraire précis dans un temps établi, l'avion ou l'hélicoptère sera dans la plupart des cas éloigné du départ de feu.
- à rechercher dans un premier temps dans les images au moins une petite zone de pixels représentant des variations temporelles de niveaux de gris particulièrement de basse fréquence,
- puis à analyser la ou chaque zone reconnue ainsi par des moyens de mesure du taux de décorrélation temporelle des pixels appartenant à cette même zone.
- courbe A : l'évolution temporelle d'un pixel "arbre en mouvement sous l'effet du vent"
- courbe B : l'évolution temporelle d'un pixel "autoroute"
- courbe "C": l'évolution temporelle d'un pixel "fumée proche"
- courbe D : l'évolution temporelle d'un pixel "fumée éloignée"
- Premièrement; il exploite la propriété selon laquelle la fumée génère un large spectre de fréquences temporelles, avec un avantage pour les basses fréquences de l'ordre de 0,1 Hz, afin de compresser l'image en retenant uniquement les pixels dont les variations présentent un excès de basses fréquences par rapport aux hautes fréquences.
- Deuxièmement, il consiste à regrouper l'ensemble des pixels retenus précédemment en objets suffisamment disjoints dans l'espace et suffisamment stables dans le temps, pour exploiter l'hypothèse selon laquelle l'objet créé par la fumée est fixe ou très faiblement mobile.
- Troisièmement, il consiste à analyser chacune des zones identifiées par l'étape précédente, pour mesurer à l'aide d'un traitement numérique décorrélation et/ou de chaoticité.
- une cartographie de la région couverte par l'ensemble des détecteurs, légèrement surdimensionnée
- l'ensemble des points et des zones de surveillance
- l'ensemble des demi-droites joignant un point de surveillance au bord de l'écran orientées dans la direction du foyer faisant l'objet d'une alarme; Cette direction est calculée simplement à partir l'abscisse et de l'ordonnée du pixel du foyer dans l'image et de l'orientation du détecteur
- les coordonnées exactes d'un foyer si plusieurs demi-droites (de plusieurs détecteurs) se coupent
- l'ensemble des petits films correspondant aux images du passé récent autour de chaque foyer , visualisés à cadence accélérée dans le prolongement des demi-droites.
Claims (7)
- Procédé de détection automatique de feux, notamment de feux de forêt, basé sur la reconnaissance de fumées à partir d'au moins une caméra vidéo (4), qui consiste à effectuer un traitement d'images fixes obtenues par la ou les caméras (4) dans le spectre visible, pour détecter et localiser un éventuel foyer de fumée, caractérisée en ce que la détection d'un tel foyer consiste :à rechercher dans une premier temps dans les images au moins une petite zone de pixels présentant des variations temporelles de niveaux de gris (G) particulièrement de basse fréquence,puis à analyser la ou chaque zone ainsi reconnue par mesure du taux de décorrélation temporelle des pixels appartenant à cette même zone.
- Procédé de détection selon la revendication 1, caractérisé en ce que l'on sélectionne, pour la recherche de la ou chaque petite zone précitée, des pixels qui présentent, en ce qui concerne les variations temporelles de leurs niveaux de gris (G), des fréquences comprises entre 0,3 et 0,1 Hz.
- Procédé de détection selon la revendication 1 ou 2, caractérisé en qu'il comprend l'opération de recherche, dans les images, d'une petite zone de pixels présentant des variations de niveaux de gris (G) particulièrement chaotiques, par des moyens de mesure d'indice de chaocité spatio-temporelle des différentes zones de pixels dans l'image.
- Procédé de détection selon l'une quelconque des revendications 1 à 3, caractérisé en ce qu'il comprend encore une mesure du bruit spatio-temporel.
- Procédé de détection selon l'une quelconque des revendications 1 à 4, caractérisé en ce qu'il est mis en oeuvre par au moins un dispositif de détection local (2), implanté sur une étendue à surveiller (1) ou à la périphérie de celle-ci, et comprenant au moins une caméra vidéo fixe (4)connectée à une unité de traitement autonome (5) analysant l'image de la caméra (4).
- Procédé de détection selon la revendication 5, caractérisé en ce qu'un ou plusieurs dispositifs de détection (2) sont reliés à une unité centrale (10) située à distance, servant de poste de contrôle et de commande, notamment équipée de moyens de visualisation (12,13) pour un opérateur humain.
- Procédé de détection selon la revendication 6, caractérisé en ce que le poste de contrôle et de commande (10) est prévu pour la visualisation d'une séquence d'images de la partie du paysage située autour d'un foyer détecté, ladite séquence étant visualisée à une cadence fortement accélérée (18) par rapport à sa cadence réelle d'acquisition (17).
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
FR9609030A FR2750870B1 (fr) | 1996-07-12 | 1996-07-12 | Procede de detection automatique de feux, notamment de feux de forets |
FR9609030 | 1996-07-12 |
Publications (2)
Publication Number | Publication Date |
---|---|
EP0818766A1 EP0818766A1 (fr) | 1998-01-14 |
EP0818766B1 true EP0818766B1 (fr) | 2002-03-27 |
Family
ID=9494204
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP19970420115 Expired - Lifetime EP0818766B1 (fr) | 1996-07-12 | 1997-07-11 | Procédé de détection automatique de feux, notamment de feux de forêts |
Country Status (3)
Country | Link |
---|---|
EP (1) | EP0818766B1 (fr) |
DE (1) | DE69711283D1 (fr) |
FR (1) | FR2750870B1 (fr) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102708353A (zh) * | 2010-12-27 | 2012-10-03 | 财团法人工业技术研究院 | 火焰判断方法、火焰判断系统与火焰判断装置 |
US11080990B2 (en) | 2019-08-05 | 2021-08-03 | Factory Mutual Insurance Company | Portable 360-degree video-based fire and smoke detector and wireless alerting system |
Families Citing this family (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
FR2775534B1 (fr) * | 1998-02-27 | 2000-09-15 | D Aviat Latecoere Soc Ind | Dispositif de surveillance d'une enceinte, notamment de la soute d'un avion |
US6529132B2 (en) | 1998-02-27 | 2003-03-04 | Societe Industrielle D'avation Latecoere | Device for monitoring an enclosure, in particular the hold of an aircraft |
US6184792B1 (en) * | 2000-04-19 | 2001-02-06 | George Privalov | Early fire detection method and apparatus |
EP1364351B8 (fr) | 2001-02-26 | 2006-05-03 | Fastcom Technology S.A. | Procede et dispositif de detection de feux base sur l'analyse d'images |
PT102617B (pt) | 2001-05-30 | 2004-01-30 | Inst Superior Tecnico | Sistema lidar controlado por computador para localizacao de fumo, aplicavel, em particular, a deteccao precoce de incendios florestais |
GB2388895B (en) * | 2002-05-20 | 2004-07-21 | Infrared Integrated Syst Ltd | Improved detection of turbulence in fluids |
GR1004455B (el) * | 2003-02-21 | 2004-02-17 | Δουκασαχριστοσα | Ανιχνευτησαπηγωναθερμοτητος |
DE202005021248U1 (de) * | 2005-04-21 | 2007-10-04 | Entwicklungsgesellschaft für Systeme und Technologien der Telekommunikation mbH | Vorrichtung zur nächtlichen Erkennung von Bränden |
CN109544842A (zh) * | 2018-12-29 | 2019-03-29 | 许昌学院 | 一种森林防火地理信息系统 |
CN111539239B (zh) * | 2019-01-22 | 2023-09-22 | 杭州海康微影传感科技有限公司 | 明火检测的方法、装置及存储介质 |
CN115376268B (zh) * | 2022-10-21 | 2023-02-28 | 山东太平天下智慧科技有限公司 | 一种基于图像识别的监控报警消防联动系统 |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
ES2070710B1 (es) * | 1993-02-10 | 1997-05-01 | Nacional Bazan De Construccion | Sistema de vigilancia y deteccion de focos de calor en areas abiertas . |
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1996
- 1996-07-12 FR FR9609030A patent/FR2750870B1/fr not_active Expired - Fee Related
-
1997
- 1997-07-11 EP EP19970420115 patent/EP0818766B1/fr not_active Expired - Lifetime
- 1997-07-11 DE DE69711283T patent/DE69711283D1/de not_active Expired - Lifetime
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102708353A (zh) * | 2010-12-27 | 2012-10-03 | 财团法人工业技术研究院 | 火焰判断方法、火焰判断系统与火焰判断装置 |
CN102708353B (zh) * | 2010-12-27 | 2015-01-07 | 财团法人工业技术研究院 | 火焰判断方法、火焰判断系统与火焰判断装置 |
US11080990B2 (en) | 2019-08-05 | 2021-08-03 | Factory Mutual Insurance Company | Portable 360-degree video-based fire and smoke detector and wireless alerting system |
Also Published As
Publication number | Publication date |
---|---|
DE69711283D1 (de) | 2002-05-02 |
EP0818766A1 (fr) | 1998-01-14 |
FR2750870A1 (fr) | 1998-01-16 |
FR2750870B1 (fr) | 1999-06-04 |
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