Patent Publication Number: US-10310030-B2

Title: Method for automatically recognising a magnetic object

Description:
RELATED APPLICATIONS 
     This application is a U.S. National Stage of international application number PCT/EP2014/0753776, filed Feb. 26, 2014, which claims the benefit of the priority date of French Patent Application FR 1352129, filed Mar. 8, 2013, the contents of which are herein incorporated by reference. 
     FIELD OF INVENTION 
     The invention relates to a method and an apparatus for automatically recognizing a magnetic object. The invention relates also to an information storage medium for implementing this method. 
     BACKGROUND 
     Here, “magnetic object” denotes an object comprising one or more magnetic parts made of a magnetic material. A same magnetic part is generally a single block of magnetic material. A magnetic material is a material which exhibits magnetic properties that can be measured by an apparatus for automatically recognizing magnetic objects. 
     There are many situations in which it is desirable to be able to automatically recognize an object. For example, this may be useful for modifying the operation of a machine, such as a robot, or for automatically triggering an action according to the recognized object. Moreover, many objects already include magnetic parts. It is also very easy to add a magnetic part, such as, for example, a permanent magnet, to any object. 
     Prior art is known from U.S. Pat. No. 6,841,994B1 and FR2952450A1. 
     SUMMARY OF INVENTION 
     The subject of the invention is therefore a method for automatically recognizing a magnetic object according to claim  1 . 
     The use of an array of magnetometers separated from one another by a distance less than the maximum separation between the magnetic parts of the magnetic object furthest apart makes it possible to measure a very accurate magnetic signature of this object. This method is then particularly effective for recognizing the magnetic object because it makes it possible to distinguish magnetic objects which resemble one another. For example, experimental results show that this method makes it possible to recognize and distinguish an iPhone5® telephone from an iPhone4 ® telephone without any modification being made to these cell phones. 
     The embodiments of this method can include one or more of the features of the dependent claims. 
     These embodiments of the method also offer the following advantages:
         the holding of the magnetic object at a distance less than the distance d max  defined above and, preferably less than 50 cm, makes it possible to very significantly improve the recognition of the magnetic object;   the rotation or the translation of the signature S m  or S Ref  to find the minimum value of the deviation E makes it possible to make the recognition method more robust with respect to errors of positioning of the magnetic object to be recognized relative to the predetermined position in which the signature of the known object was recorded;   using an array of magnetometers in which the fixed distance between two immediately consecutive magnetometers is less than the maximum separation between the two magnetic parts furthest away from one another of the magnetic object makes it possible to further improve the accuracy of the measurement in the step c) and therefore the recognition of the magnetic object;   using an array of magnetometers in which the magnetometers are distributed along at least two non-parallel directions makes it possible to improve the recognition of the magnetic objects.       

     Another subject of the invention is an information storage medium according to claim  8 . 
     Another subject of the invention is an apparatus for recognizing a magnetic object according to claim  9 . 
     The invention will be better understood on reading the following description, given purely as a nonlimiting example and with reference to the drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a schematic illustration of an identification system comprising an object to be recognized and an apparatus for automatically recognizing magnetic objects; 
         FIG. 2  is a schematic and partial illustration of an array of magnetometers used in the recognition apparatus of the system of  FIG. 1 ; 
         FIG. 3  is a schematic illustration of a database used in the recognition apparatus of the system of  FIG. 1 ; 
         FIG. 4  is a flow diagram of a method for automatically recognizing a magnetic object using the system of  FIG. 1 . 
     
    
    
     In these figures, the same references are used to denote the same elements. 
     DETAILED DESCRIPTION 
     Hereinafter in this description, the features and the functions well known to those skilled in the art are not described in detail. 
       FIG. 1  represents an identification system  2 . The system  2  comprises a magnetic object  4  to be recognized and an apparatus  6  for automatically recognizing magnetic objects. 
     Typically, the object  4  can be moved directly by the hand of a human being. To this end, the object  4  generally weighs less than 10 kg and, preferably, less than 1 kg or 250 g. For example, the dimensions of the object  4  are small enough for it to be able to be grasped and moved by a single hand of a user. 
     The object  4  comprises at least one magnetic part, that is to say made of a magnetic material. This magnetic part is capable of distorting the field lines of the Earth&#39;s magnetic field. Here, the magnetic material has a static relative permeability pr different from one. Preferably, it is a ferromagnetic or ferrimagnetic material. 
     A magnetic object can comprise a single magnetic part or, on the contrary, a plurality of distinct magnetic parts secured to one another. The different magnetic parts can be mechanically fixed to one another with no degree of freedom or, on the contrary, with one or more degrees of freedom. Each of these magnetic parts can acquire a magnetization, and therefore exhibit a non-zero magnetic moment, only in the presence of an external magnetic field such as the Earth&#39;s magnetic field or, on the contrary, exhibit a permanent magnetization. A permanently magnetized magnetic part is also called a permanent magnet. A permanent magnet exhibits a non-zero magnetic moment even in the absence of external magnetic field. Typically, the permanent magnet is made from a magnetic material with a coercive magnetic field greater than 100 A·m −1  or 500 A·m −1 . The strength of this permanent magnet can be greater than 0.01 A·m 2  or 0.1 A·m 2 . When the magnetic object comprises a plurality of permanent magnets, it is also preferable for the ratio between the strengths of these permanent magnets to be less than 10 or 5 and, advantageously, less than 2 or 1.5 or equal to 1. 
     Here, the object  4  essentially comprises two magnetic parts  10  and  12  that are immobile relative to one another. For example, they are fixed with no degree of freedom to one and the same frame of the object  4 . Here, the frame is made of a non-magnetic material. A non-magnetic material does not exhibit any magnetic property that can be measured by the apparatus  6 . 
     Given that the magnetic parts  10  and  12  are fixed in the object  4 , the relative distances between the magnetic dipoles corresponding to the parts  10  and  12  and the angles between these magnetic moments are constant. Similarly, in this embodiment, the number of magnetic parts in the object  4  and the magnetic moments of these parts are assumed constant. 
     Here, the object  4  is a cell phone. In the case of a cell phone, the two magnetic parts  10  and  12  are formed, respectively, by the microphone and the loudspeaker of the telephone. In effect, these parts include permanent magnets. 
     The apparatus  6  makes it possible to measure the Earth&#39;s magnetic field distorted by the presence of the object  4 . To this end, the apparatus  6  includes an array of N tri-axial magnetometers M ij . In  FIG. 1 , the vertical wavy lines indicate that a part of the apparatus  6  has not been represented. 
     Typically, N is greater than 5 and, preferably, greater than 16 or 32. Here, N is greater than or equal to 64. 
     In this embodiment, the magnetometers M ij  are aligned in rows and in columns to form a matrix. Here, this matrix comprises eight rows and eight columns. The indices i and j respectively identify the row and the column of this matrix at the intersection of which the magnetometer M ij  is located. In  FIG. 1 , only the magnetometers M i1 , M i2 , M i3 , M i4  and M i8  of a row i are visible. The position of the magnetometers M ij  relative to one another is described in more detail with reference to  FIG. 2 . 
     Each magnetometer M ij  is fixed with no degree of freedom to the other magnetometers. To this end, the magnetometers M ij  are fixed with no degree of freedom onto a rear face  22  of a horizontal rigid plate  20 . This rigid plate has a front face  24  turned toward the object  4 . The plate  20  is made from a rigid non-magnetic material. For example, the plate  20  is made of glass. 
     Preferably, the plate  20  also comprises, on its front face, a device  26  for assisting in the placement of the object  4 . This device  26  helps the user to position and hold the object  4  in a predetermined position relative to the magnetometers M ij . The device  26  is, for example, a template of the object. This template includes a drawing on the face  24  of the outline of the object  4  or a hollowed-out imprint of the object  4 . 
     Each magnetometer M ij  measures the direction and the amplitude of the magnetic field generated or disturbed by the object  4 . For that, each magnetometer M ij  measures the norm of the orthogonal projection of the magnetic field at this magnetometer M ij  on three measurement axes of this magnetometer. Here, these three measurement axes are mutually orthogonal. For example, the measurement axes of each of the magnetometers M ij  are, respectively, parallel to the directions X, Y and Z of an orthogonal reference frame XYZ. The reference frame XYZ is fixed with no degree of freedom to the apparatus  6 . Here, the directions X and Y are horizontal and the direction Z is vertical. Here, b ij  denotes the vector whose coordinates are formed by the measurements x ij , y ij  and z ij , where x ij , y ij  and z ij  are the measurements of the magnetometer M ij  on its measurement axes parallel, respectively, to the directions X, Y and Z 
     The sensitivity of the magnetometer M ij  is for example equal to or less than 4*10 −7  T. 
     Each magnetometer M ij  is connected via an information transmission bus  28  to a processing unit  30 . 
     The processing unit  30  is suitable for implementing the method of  FIG. 4 . In particular, from the measurements of the magnetometers M ij , the unit  30  is capable of recognizing the magnetic object presented in front of the apparatus  6  by comparison to a database  36  of magnetic signatures of known objects. This database  36  is described in more detail with reference to  FIG. 3 . To this end, the unit  30  comprises a programmable electronic computer  32  suitable for executing instructions stored on an information storage medium. The unit  30  therefore also comprises a memory  34  containing the instructions necessary for the execution by the computer  32  of the method of  FIG. 4 . The database  36  is stored in the memory  34 . 
       FIG. 2  represents some of the magnetometers M ij  of the apparatus  6 . These magnetometers M ij  are aligned in rows i parallel to the direction X. These magnetometers are also aligned in columns j parallel to the direction Y to form a matrix. The rows i and the columns j are arranged in ascending index order. 
     The surface area occupied by the array of magnetometers is typically less than 100 m 2  and, preferably, less than 5 m 2  or 1 m 2  or 50 cm 2 . 
     The center of the magnetometer M ij  is located at the intersection of the row i and of the column j. The center of the magnetometer corresponds to the point where the magnetic field is measured by this magnetometer. Here, the indices i and j belong to the range [1; 8]. 
     The centers of two immediately consecutive magnetometers M ij  and M i,j+1  along a row i are separated by a known distance d i,j,j+1 . Similarly, the center of two immediately consecutive magnetometers M ij  and M i+1,j  along a same column j are separated by a known distance d j,i,i+1 . 
     In the particular case described here, whatever the row i, the distance d i,j,j+1  is the same. This distance is therefore denoted d j . Similarly, whatever the column j, the distance d j,i,i+1  between two magnetometers is the same. This distance is therefore denoted d i . 
     Here, the distances d i  and d j  are both equal to d. 
     The distance d is less than, and preferably at least two times smaller than, the maximum separation between the magnetic parts of the magnetic object to be recognized furthest away from one another. Here, this distance d is therefore less than the shortest distance which separates the parts  10  and  12 . 
     Typically, the distance d is between 1 and 4 cm when:
         the strength of each permanent magnet likely to be contained in the object to be recognized is less than 2 A·m 2  or 1 A·m 2  or 0.5 A·m 2  and, preferably, greater than 0.1 A·m 2  or 0.2 A·m 2 ,   the sensitivity of the magnetometers is 4*10 −7  T, and   the number of magnetometers M ij  is sixty four.       

       FIG. 3  represents in more detail the database  36 . This database  36  contains the magnetic signatures of several known magnetic objects. Here, it is represented in the form of a table. 
     For each known object, the database  36  includes, in a column  40 , an identifier “Ref” of this known object. The identifier “Ref” uniquely identifies this known object out of all the known objects stored in the database  36 . Each identifier “Ref” is associated by the base  36  with a prestored magnetic signature S Ref  of this known object. The signature S Ref  is contained in the column  44 . 
     The magnetic signature of an object comprises distinctive characteristics making it possible to identify this object out of all the known objects indexed in the database  36 . Here, it comprises the union of the vectors b ij  measured at the same time by each of the magnetometers M ij . A magnetic signature of an object is therefore the set of the vectors: {b 11 , b 12 , . . . , b ij , b i,j+1 , . . . b i+1, j , b i+1,j+1 , . . . , b N,N }. Hereinbelow, to distinguish the vectors and the measurements contained in the signature of a known object “Ref” from those contained in the signature of an object to be recognized, the identifier “ij” of the magnetometer M ij  is followed by the index “Ref” in the case of the vectors and measurements contained in the signature S Ref . Conversely, the identifier “ij” of the magnetometer M ij  is followed by the index “m” in the case of the vectors and measurements contained in the signature S m  of the object to be recognized. Thus, with these notations, the vector b ij,Ref  and the measurements x ij,ref  designate, respectively, the vector b ij  and the measurement x ij  obtained from the magnetometer M ij  and contained in the signature S Ref . The vector b ij,m  and the measurement x ij,m  designate, respectively, the vector b ij  and the measurement x ij  obtained from the magnetometer M ij  and contained in the signature S m . 
     The operation of the system  2  will now be described with reference to the method of  FIG. 4 . 
     This method begins with a phase  70  of storing magnetic signatures S Ref  of several known magnetic objects in the database  36  and associating a known object identifier with each of these signatures. 
     For that, for example, in a step  72 , the known object is placed in front of the face  24  in a predetermined position and it is held immobile in this position throughout the next step. The predetermined position is chosen in such a way that, in that position, the shortest distance between at least four of the magnetometers M ij  and the known object is less than d max . d max  is equal to [μ 0 m/4πσ10 (SNR/20) ] 1/3 , where:
         σ is the standard deviation of the noise of the magnetometers,   μ 0  is the permeability of the vacuum,   m is the magnetic moment of the magnetic object, and   SNR is a constant equal to 6.02 db.       

     Typically, for the objects that are to be recognized, d max  is equal to or smaller than 50 cm or 30 cm. 
     To this end, the known object is placed in the template of the device  26 . For example, it is held immobile in this template simply by the force of gravity. 
     Then, in a step  74 , the magnetometers M ij  simultaneously measure the magnetic field in the presence of the known object. Preferably, the step  74  is reiterated several times, for example more than 10 or 50 times, to obtain several measurements for each magnetometer M ij . Then, it is the average of these measurements for each magnetometer M ij  which is processed in the subsequent steps. That makes it possible to filter some of the noise of the measurements. The step  74  typically lasts less than a second. 
     In a step  76 , the unit  30  constructs the magnetic signature S Ref  of the known object from the measurements carried out in the step  74 . This signature S Ref  notably comprises the union of the vectors b ij,Ref  measured in the step  74  by all the magnetometers M ij . 
     In a step  78 , the signature S Ref  is stored in the database  36  associated with the identifier “Ref” of the known object. 
     The steps  72  to  78  are then reiterated for a large number of known objects different to one another in order to populate the database  36 . The steps  72  to  78  can also be reiterated for the same known object but placed in a different position with respect to the magnetometers M ij . In effect, the presence of the device  26  limits the number of possible positions of the object relative to the magnetometers M ij  but does not necessarily prohibit several predetermined positions for the same object. For example, in the case of a cell phone, the latter can be positioned inside the template with its screen turned toward the face  24  or turned away from the face  24 . It can also be positioned in the template with its microphone situated on the left or on the right. Thus, the template allows four predetermined positions for a cell phone. However, it is not always necessary to store a signature S Ref  for each possible predetermined position of the known object. In effect, as explained below, it is possible to recognize an object even if the latter is not placed exactly in the same predetermined position as that used to record the signature S Ref . 
     By way of example, the signatures of the following objects are stored in the database  36  in the phase  70 :
         the object  4 ,   a cell phone of a brand other than that of the object  4 ,   a stapler,   a screwdriver,   a pen fitted with at least one permanent magnet,   a brush fitted with a permanent magnet of a strength greater than that of the magnet of the pen,   a bulb, and   a laptop computer.       

     Once the database  36  has been populated with several magnetic signatures of known objects, a phase  100  of automatic recognition of an unknown object can then be carried out. The unknown object is chosen from the objects whose signatures were stored in the phase  70 . Subsequently, it is assumed that this unknown object is the object  4 . 
     The phase  100  begins with three steps  102  to  106  that are identical, respectively, to the steps  72  to  76 , except that it is the unknown object which is placed in front of the face  24 . At the end of the step  106 , it is therefore the signature S m  of the object  4  which is obtained. 
     In a step  108 , the unit  30  computes a deviation E between the signature S m  and a signature S Ref  prestored in the database  36 . The deviation E is representative of the resemblance between the signatures S m  and S Ref . Here, the greater this resemblance, the smaller the deviation E. 
     In this embodiment, the following steps are based on the analogy which exists between a magnetic signature constructed by the unit  30  and a matrix image. To this end, each magnetic signature is stored in a file in the format of a matrix image. For example, the format used is the format known by the term “bitmap”. For that, each magnetometer M ij  is likened to a sensor making it possible to measure the equivalent of a “color”, the “color” here being the measurements x ij , y ij  and z ij  of the magnetometer M ij . More specifically:
         the indices ij which identify the position of the magnetometer M ij  in the reference frame X, Y, Z correspond to the position of the pixel in the image, and   the measurements x ij , y ij  and z ij  of the magnetometer M ij  code the color of the pixel for example, in an RGB (red green blue) coding.       

     Here, each pair of indices “ij” is associated with the coordinates a ij , b ij  and c ij  of the magnetometer M ij  in the reference frame XYZ. 
     Subsequently, each file containing a magnetic signature in a matrix image format is called “magnetic image”. The file containing the signatures S m  or S Ref  are designated, respectively, by images I m  and I Ref . In these files, each pixel P ij  corresponds to a respective magnetometer M ij . From the moment when the signatures S m  and S Ref  are stored in the format of a matrix image, it is possible to use the same known algorithms as those used in image processing to compute the correlation between the files I m  and I Ref  and therefore between the signatures S m  and S Ref , and also the minimum deviation E between these signatures. These algorithms are not therefore described here in detail. 
     For example, the unit  30  applies a transformation to the image I m  to obtain a transformed image I t  which minimizes the value of the deviation E. Typically, this transformation is a composition of translations and of rotations. For example, the translations applied to the pixels of the image I m  are translations parallel to the plane XY. The rotations applied to the pixels of the image I m  are rotations about an axis parallel to the direction Z or rotations of 180° relative to an axis belonging to the plane XY. 
     The deviation E is for example computed using one of the following formulae: 
     
       
         
           
             
               
                 
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     At the end of the step  108 , the value of the deviation E is the value obtained with the transformation of the image I m  which minimizes this deviation. The use of an algorithm which makes it possible to find the transformation which best correlates the signatures S m  and S Ref  makes the recognition method robust with respect to errors of positioning of the object  4  relative to the predetermined position in which the signature S Ref  was stored. 
     Then, in a step  110 , the deviation E is compared to a predetermined threshold L 1 . If the deviation E is greater than the threshold L 1 , the steps  108  and  110  are reiterated with a new signature S Ref . If, however, the steps  108  and  110  have already been executed for all the signatures S ref  contained in the database  36 , without the object  4  having been able to be recognized, then the procedure is stopped, and the unit  30  indicates that the object  4  has not been recognized. 
     If the error E is less than the threshold L 1 , the object  4  corresponds to the known object “Ref”. In response, in a step  112 , the unit  30  communicates this information to a software module responsible for executing a specific operation in response to the recognition of the object  4 . For example, this software module communicates the identifier “Ref” of the recognized object to a human being via a human-machine interface. This software module may also automatically trigger an action in response to the recognition of this object such as, for example, the control of an external electronic peripheral device. 
     Many other embodiments are possible. For example, the magnetic parts of the object to be recognized may participate in the operation of this object. Such is, for example, the case when the magnetic parts are the permanent magnets of the loudspeaker and of the microphone of a cell phone. However, the magnetic parts can also be added to the object to be recognized in order to allow it to be recognized by the apparatus  6 . For example, different permanent magnets are added to utensils normally without any magnetic part, such as a pencil and an eraser. The apparatus  6  can then recognize them. 
     The magnetometers can have more than three measurement axes. However, even when a magnetometer has more than three measurement axes, this magnetometer is here also qualified as “tri-axial” magnetometer because it comprises at least three non-collinear measurement axes. 
     The distance between the magnetometers does not need to be known. It is sufficient for it to be constant for the recognition of the magnetic object to be able to be implemented. 
     The magnetometers M ij  are not necessarily arranged in a same plane. As a variant, the magnetometers are arranged in a three-dimensional space. In this space, the position of each magnetometer is identified by the coordinates a ij , b ij  previously defined and, in addition, by a coordinate cu along the direction Z of the reference frame X, Y, Z. In this variant, the value of the coordinate c ij  is not the same for all the magnetometers. Conversely, in an extremely simplified case, all of the magnetometers of the array are aligned along a same rectilinear axis. 
     As a variant, the device  26  for assisting in the positioning of the magnetic object to be recognized is omitted. Conversely, in another embodiment, this device  26  can be replaced by a more efficient assisting device, for example including mechanical polarizers which allow the object to be recognized to be positioned only in one of the predetermined positions where a magnetic signature S Ref  of the same object has already been prestored in the database  36 . 
     The storage phase  70  can be carried out differently. For example, the signatures S Ref  are constructed from measurements supplied by an apparatus other than the apparatus  6 . In this case, this other apparatus includes the same matrix of magnetometers M ij . 
     As a variant, the magnetic signature of an object comprises only the vectors b ij  whose amplitude exceeds a predetermined threshold, for example, several times greater than the level of the ambient noise. 
     The magnetic signature of an object can change according to its state of use. For example. The amplitude of one of the magnetic moments of the object may vary over time between a state in which the object  4  is powered or switched on and a state in which the object  4  is off or not powered. In this case, one solution is to store in the database  36  a first magnetic signature of the object when it is on and a second signature when it is off. Thus, in addition to recognizing the object, this also makes it possible to indicate whether it is off or on. 
     The measurements of the magnetometers can be stored in a first stage. Then, the steps  76 ,  78  or  104  to  112  are carried out later at a time when the magnetic object is no longer present in front of the face  24  of the array of magnetometers. Similarly, the execution of the method of  FIG. 4  can be distributed over several electronic computers. For example, the steps  108  to  112  are executed by a programmable electronic computer distinct from the computer which executes only the steps  102  to  106 . The processing unit  30  then comprises all of these computers. 
     The step  108  can be carried out differently. For example the image I Ref  is transformed and not the image I m . 
     The step  108  can be simplified if the magnetic object to be recognized is always placed in one of the predetermined positions where a signature S Ref  has been stored in the database  36 . In this case, it is possible to proceed directly with the computation of the value of the deviation E using one of the relationships (1), (2), or (3) without trying to best fit the image I m  to the image I Ref . 
     As a variant, a filtering of recognition results can be added. For that, the phase  100  is reiterated several times for the same object to be recognized. In the step  112 , the object is considered to be recognized only if the same object has been recognized at the end of more than 50% or 80% of the iterations of the phase  100 . 
     The value of the threshold L 1  can be a constant independent of the results of the preceding steps, or, on the contrary, be predetermined as a function of the preceding iterations of the steps  108  and  110 . For example, the value of the threshold L 1  is replaced by the value of the deviation E each time the value of this deviation is smaller than that of the threshold L 1 . In this case, the object which is recognized systematically corresponds to that for which the value of the deviation E is minimum.