SCANNING ARRANGEMENT AND METHOD

Abstract: A scanning arrangement comprising means (40) for projecting a two-dimensional optical pattern on a surface (35) of a scanned object and a two-dimensional photodetector (34') is mounted within a hand-held scanning device and outputs scan files of 3D coordinate data of overlapping surface portions of the object. The surface portions defined by these scan files are registered by appropriate rotations and translations in a computer, which are determined either from the outputs of a gyroscope (51) and an accelerometer (50) or by mathematical processing of the surface portions e.g. involving detection and location of common features.

Description: Scanning arrangement and method The present inv ention relates to a scanning arrangement and method for determining the shape, size or other three-dimensional surface characteristics of an object, such as colour for example. A number of patents and published patent applications disclose optical scanning systems w hich rely on a scanned laser beam or the like for determining the shape ol an object. Usually such systems utilise a fixed mounting for the scanmng system and 0 utilise optical tπangulation for determining depth information. Examples ot such systems include US 4,627,734 (Rex), EP-B-233,920 (Addleman) and WO 94/ 15173 (Crampton). 5 There is a need for a scanner for determining shape or other surface characteristics w hich can be hand-held. As far as we are aware, only one such system is known, namely that disclosed in US 5,198,877 (Schulz) and its equivalent EP-A-553,,266. The Schulz system requires an externally generated coordinate system defined by an 0 array of photodetectors which detects an array of pilot lights on the scanner. Hence the scanner can only be used within this coordinate system and furthermore the array of pilot lights must be kept in \ ιew by the-array of photodetectors, which further restricts the mobility of the scanner. This is a seπous disadvantage because it is $ normally necessary to scan the object of interest from all sides in order to build up a complete picture of its surface. An object of the present invention is to provide a scanning arrangement and method in w hich the scanner can be moved freely without reference to the position of its 0 mounting. Accordingly the invention provides a scanmng arrangement for determining the shape or other three-dimensional surlace characteristics of an object, the arrangement comprising a scanning device which is freely movable relative to said object, the ice compπsing: a) an optical projector for projecting a predetermined pattern onto a region of the surface of the object, and b) an optical detector for detecnng the coordinates or other surface 0 characteristics of said region and for generating output signals representative ot such coordinates or other surface characteristics, the arrangement further including: c) processing means coupled to said detector for generaung a set of output data representing said surface characteristics of a scanned portion of the surface of said object, d) combining means coupled to said processing means for combining sets of such Q output data derived from o erlapping scans of said surface into a common set of output data by appropnate rotations and translations, said combining means optionally including further processing means for calculaung said rotauons and translations from subsets of respectiv e sets of such output data w hich relate to a common area of said surface, - ■ e) opuonally, inertia! sensing means for detecting movement of said scanning de ice relative to said object and generating output signals representative of such mov ement, and t) correcting means for correcting for movement of said scanning device relau e to said object between successi e scans, said correcting means being responsi e to at least one of: 1) output signals from said inertial sensing means (if present) π) output data from said further processing means (if present), the arrangement including either said ertial sensing means or said further processing means or both. In one embodiment the scanning device carries inertial sensing means for sensing 10 its linear acceleration and rotation sensing means for sensing its rate ol rotation By double integrating the output of the inertial sensing means ith respect to time and integrating the output of the rotational sensing means w ith respect to time the position and attitude of the scanning device can be detected throughout the 15 scanning process and these parameters can be applied by the correcting means to correct the output of the optical detector. In another embodiment the correcting means eftectiv ely consists of the combining means, w hich in this embodiment compnses further processing means for 20 determining the translations and/or rotations required to combine the data f rom successive scans. The inv ention also provides a method of determining the shape or other three- dimensional surface characteristics of an object by means of a scanning dev ice 2." hich is freely movable with respect to the object, the method compπsmg: l) projecting from the scanning device a predetermined optical pattern onto a region of the surface of the object, n) optically detecung the coordinates or other surface characteristics of said region 0 w ith an optical detector mounted on said scanning dev ice, in) deriving a set of output data representing said coordinates or other surface character! sties of said region, ι ) repeatedly scanning said optical pattern over said object in o erlapping fashion and denv ing further sets of output data from overlapping scans, and -^ ) correcting said sets of output data for movement of said scanning dev ice relative to said object between successive scans either by sensing movement of said scanning dev ice relative to said object with an inertial sensing means (50, 51 ) or by determining the rotations and or translations needed to superimpose subsets of 0 respectiv e sets of said output data which relate to an area of said surface which is common to said sets. Preferred features are defined in the dependent claims. Preferred embodiments of the present in ention will now be described by way of example only w ith reference to Figures I to 6 of the accompanying drawings, in w htch: Figure 1 is a schematic perspectiv e v iew of one scanning device (utilising a linear 50 scanning pattern) in accordance with the invention, showing the geometry of the optical sy stem; Figure 2 is a block diagram of the scanning arrangement utilising the scanning dev ice of Figure 1 ; Figure 3 is a plan v iew showing the optics of another scanning device (utilising a two-dimensional scanning pattern) for use in a scanning arrangement in accordance w ith the inv ention; Figure 4 is a flow diagram show ing the image processing earned out by the arrangement of Figure 2; Figure 5 is a sketch perspectiv e v iew illustrating the projection of ov erlapping scanning patterns by the scanning dev ice of Figure 3, and Figure 6 is a sketch perspectiv e v iew illustrating a method of registeπng ov erlapping scanned surface portions The generally T-shaped scanning dev ice 10 show n schematically in Figure 1 is hand held and compπses a projector w hich generates a v ertical fan-shaped beam ot light 3 onto an object 1 of unknow n shape and a lens 33 w hich collects diffusely 10 reflected light 4 from the illuminated region of the object and images the projection 13 of this beam on the object's surface onto a tw o-dimensional photodetector 34 The beam 3 is generated by a laser 29 (w hich is preferably a semiconductor laser ith beam-shaping optics but may be a He-N ' e laser for example) and a cylindrical 1 lens 30 and the photodetector 34 may consist of a two-dimensional CCD array w ith sev eral hundred photosensitive elements along each dimension for example In an another embodiment (not show n) the scanmng dev ice can be generally C-shaped, hav ing the beam generator in one limb, the photodetector in the other and a gnp between the two limbs, and can be used with the gnp approximately v ertical and 20 the tan-shaped beam approximately hoπzontal. In order to maximise depth of field and simplify the geometry of the arrangement, the photodetector 34 is inclined in the honzontal (z-x) plane at an angle β to the x- 25 v plane, w hose normal is parallel to the optical axis of the lens 33, β being such that the Scheimpflug condition is satisfied. In this condition, the image of the photodetector 34 is projected by lens 33 into the plane of fan-shaped beam 3 and the image 13' formed on the photodetector 34 corresponds to the profile of the 30 object surface as v iewed at a πght angle to the plane of beam 3. For example a πdge 1 1 is shown on the front of the object and this feature is clearly visible in the image 13 of the profile. Except when the magnification of the lens 33 is unity (so that the projection stπpe 13 and image 13' are symmetπcally located on either side ^ of lens 33) the image 13 is a distorted representation of projection stπpe 13 and in general the range magnification MR (the ratio of hoπzontal displacement of an image point on the photodetector to hoπzontal displacement of the coπesponding projection point in the plane of beam 3) is given by MR = Mj_sιn g w here ML IS the lateral magnification and g is the angle in the hoπzontal plane between the optical 40 axis of the lens 33 and the beam 3. The Scheimpflug condition is discussed in Rex et al, OPTICAL ENGINEERING, December 1987 Vol 26 No 12 p 1245 and is illustrated in Figures 2 and 3 ot that 45 paper, w hich is incorporated herein by reference. Accordingly it w ill be apparent to persons skilled in the art of optical engineeπng that the profile of the surface of the object 1 (as v iewed at πght angles to the plane of beam 3) can be denved from the output of the photodetector 34. 50 In use, the scanning dev ice 10 is used to sweep the stπpe 13 ov er the entire surface ot object 1 Dunng this process, the changes in angular oπentation ot the scanning dev ice are detected by a v ibratory gyroscope 51 w hich generates output signals ΛJ> φ \ , φ \ , φz indicativ e of the rate of rotation of scanning dev ice 10 about axes x, y and z " respecuv ely . Miniature v ibratory gyroscopes are commercially av ailable at low cost and rely on Coπolis forces set up in a v ibrating shell or other structure. Similarly, the acceleration of the scanmng device along the x, y and z axes is detected by an accelerometer 50 which generates respectiv e acceleration signals a , ay and az respectively. Preferably the sensitive axes of the gyroscope 51 are close to the centre of photodetector 34 in order to simplify subsequent computauon but this is not essential. The scanning device also includes a tπgger switch T which is operable by the user to start and stop the acquisition of data from the photodetector. This tπgger switch T outputs control signals c. It is also within the scope of the invention to locate the accelerometer and gyroscope on the object 1 and to keep the scanmng device stationary w hilst manoeuvπng the object so as to sweep the stπpe 13 across the surface of the object. This may be useful in cases where movement of the object is unavoidable, e.g. if the object is part of the human body such as a patient ' s head for example. The circuitry for processing the output signals from the photodetector 34, the gyroscope 51 and the accelerometer 50 is shown in Figure 2. These output signals may be conveyed to the circuitry by a flexible cable or wireless link for example or may for example be digitised and stored in local memory such as a high capacit miniature hard disc (not shown) in the scanning device, enabling the scanning device to be used remotely from its processing circuitry and enabling the processing to be earned out after scanning has been completed. At least some of the circuitry of Figure 2 may be located in the scanning device. Preferably, the generation and/or acquisition of data from the photodetector 34 is gated by signals from the gyroscope 51 and or accelerometer 50 which prevent the determinauon of position and/or attitude of the scanner under conditions m which the angular rotation or acceleration are too great or too small (e.g. as a result of noise or dnft ) to enable accurate calculations to be made. Turning no to Figure 2, the accelerometer is shown as three blocks 50a to 50c w hich output signals indicative of the acceleration along the x, y and z axes respectively and the gyroscope is similarly represented as blocks 51a to 51c which output signals indicaUve of the rate of rotation about axes x, y and z respectively. The acceleration signals are amplified by conventional low noise and dnft preamplifier circuits and fed via sample and hold circuitry 45 to an 14 bit analogue- to-digital converter 20. Similarly the rotation signals are amplified by conyenuonal lo noise and drift preamplifier circuits and fed via sample and hold circuitry 56 to a 14 bit analogue-to-digital converter 55. The sampie-and -hold circuitry 45, 55 samples at a rate of 5,000 per second. The digitised signals from analogue-to - digital converters 20 and 55 are fed to signal conditioning circuits 21 and 52 respecϋvely which include digital filters for filtering out noise, correct for non- lineanty in the accelerometer or gyroscope outputs (e.g. by employing look-up tables) and correct for drift due to temperature vaπations. The resulting data is fed to a digital signal processor 23 where corrections are made for the offsets (if any) of the sensitive axes of the gyroscope 51 from the photodetector 34 and for the distance between the accelerometer 50 and the gyroscope 51. Such corrections are necessary because, for example a sudden rotation centred on accelerometer 50 would cause a significant acceleration of photodetector 34 but would not be detected as such by the accelerometer. How ever the resulting rate of change of the rate of rotation detected by gyroscope 51 could be used, in conjunction with the known separation between the accelerometer and gyroscope and the output of the accelerometer, to calculate the acceleration of the photodetector, as will be apparent to persons skilled in the art. It should also be noted that in pπnciple, the rate of rotation and acceleration of the photodetector could be calculated from the outputs of two spaced apart gyroscopes (each sensitive about all three axes) or two spaced apart accelerometers (each sensitive along all three axes) provided that their positions relative to the photodetector were known. The processor 23 double integrates successive values of the corrected photodetector acceleration (along the x, y and z axes) by means of a double integrauon algonthm to determine the instantaneous position of the photodetector (relative to an arbitrar starting position) throughout the scan. Since the sample and hold circuits 45 and 56 are clocked at a rapid rate (e.g. 5 kHz) by clocking circuitry 57, this position sensing takes place essenually in real time. Similarly the processor 23 integrates successiv e values of the corrected photodetector rate of rotation (about the x, y and z axes) by means of an integration algonthm to determine the instantaneous orientation of the photodetector throughout the scan, again essentially in real time. The above integrations are performed on groups of 100 samples to update position and attitude 50 times per second, which matches the sampling rate of photodetector 34. The above position and orientation signals are fed to a scan data processor 25 w hich also receives digitised profiles of the surface of the object 1 from photodetector 34 v ia sample and hold circuit 26, 14 bit analogue-to-digital converter 27 and correction circuitry 28. Correction circuitry 28 corrects for any distortion in the optics of the scanning device 10 (particularly distortion by the lens 33), denves the true profile of projected stripe 13 (as viewed at right angles to the plane of beam 3) from the image 13' by applying appropriate corrections (e.g. to correct for the difference in lateral and range magnification resulting from the Scheimpflug geometry) and also determines the centroid of the image 13', hich, although represented as a line in Figure 1, will in general have a finite width and will therefore give πse to output signals from horizontally adjacent elements of the photodetector. Hence the scan data processor 25 receives signals representative of the true profile of the object 1 (as viewed at πght angles to the plane of beam 3) as well as signals representative of the attitude and position of the photodetector 4 (which bears a fixed relationship to the position and attitude of the region of beam 3 which intersects the surface of the object 1), all in real time. In principle a descπption of the shape of the entire region of the object's surface swept by the beam 3 could be deπved directly from the above data simply by applying the respective rotations and translations corresponding to each set of coordinate data sampled from photodetector 34. However it is likely that accumulated position and attitude errors will build up dunng the scanning process and furthermore it is likely that, at least dunng some points in the scanmng, the rotation and acceleration will be outside the dynamic ranges of the accelerometer and gyroscope. Accordingly, data is not acquired throughout the scanning peπod but only intermittently, either under the control of an operator-controlled switch T on the scanning device 10 or under the control of signals from the accelerometer and/or the gyroscope or for predetermined peπods for example. Such signals can for example either be used to dπve an indicator such as an LED to indicate to the operator that the acceleration and or rate of rotation are w ithin an acceptable range tor data acquisition or can be used as gating signals to block the acquisition of data e.g. by disabling the clocking signals f rom circuitry 57 to sample and hold circuit 26 Accordingly, in the presently preferred embodiment the processor 25 only applies the rotations and translations corresponding to a group of successiv e profiles to generate a surface descπption of a small region of the scanned surface and stops generating this surface descπption (w hich will be a cloud of points in a common coordinate system) under the control of the operator and/or under the control of the abov e gating signals. A further surface descπption of another surface portion will then be generated in a similar manner e.g. in response to further operation of the sw itch or release of the gating signals. In this manner, successive scan files each compπsing a cloud of points representative of a different but ov erlapping surface portion are generated. The position and attitude of the scanning dev ice 10 is monitored throughout the scanning and accordingly the position and attitude of the photodetector 34 at the beginning of the generation of each scan file is known (albeit possibly w ith some accumulated errors) and is associated w ith the three- dimensional coordinate data of that scan file. Thus each scan file consists of a three-dimensional cloud of points descπbing the surface coordinates of a region of the scanned surface, in association ith data representative of the position and oπentation of the photodetector 34 dunng the acquisition of each profile of that set. Successive scan files are output from processor 25 to a computer 47, which is provided with a display 131 and a ke\ board 130. Before descnbmg the processing earned out in computer 47, a further opucal arrangement will now be descπbed with reference to Figure 3, which shows a projector and detector which project a two-dimensional optical pattern onto the surface 35 of the object and detect an array of surface profiles of the object from this pattern. Accordingly this arrangement enables the acquisition of a set of three- dimensional coordinate data defining a surface portion of the scanned object without requiπng any position or onentaϋon signals, and can be substituted for the optical arrangement shown in Figure 1. Referring to Figure 3, a semiconductor laser 29' transmits a laser beam to an opucal arrangement 300 which may either include a cylindπcal lens arranged to form a fan-shaped beam oπented perpendicular to the plane of the drawing or a scanner such as an oscillating mirror arrangement arranged to oscillate the beam perpendicular to the plane of the drawing to form a corresponding fan-shaped env elope. The resulting fan-shaped beam or envelope is then directed by a fixed mirror onto a 24 facet polygonal mirror 40 rotating at 20,000 r.p.m. which scans a beam or env elope 3' m the plane of the drawing as shown. The profile (represented as an aπow a or b) defined by the intersection of this beam or env elope w ith the surface of the object is imaged by a lens 33 onto an inclined photodetector 34' and forms a corresponding image a' or b'. Preferably detector 34' satisfies the Scheimpflug condition in order to maximise the depth of field. Hence the profile a or b of the surface can be determined from the coπespondmg image a' or b\ In order to relate each detected profile to a common coordinate system the instantaneous onentation of the beam or envelope 3' in the plane of the drawing must be know n and accordingly the angular position of the polygonal mirror 40 is sensed by a sensor 41 w hich sends an angular position signal to a processor 42 Processor 42 samples the output of photodetector 34' in synchromsm with the position signal from 41 and each resulting profile calculated by processor 42 is aligned relative to a common coordinate system according to the angular position signal. Hence the output of processor 41 is a cloud of points in a three-dimensional coordinate system which define the surface portion scanned by beam 3'. Preferably arrangement 300 includes a scanner which oscillates the laser beam rapidly perpendicular to the plane of the drawing (e.g. at 8kHz), relative to the rate of oscillation of the resulting envelope 3' in the plane of the drawing and the photodetector 34' is a two-dimensional lateral effect photodiode. Such an arrangement has a v ery short response time and can generate an effectiv ely instantaneous "snapshot" of the scanned portion of the surface before the scanmng dev ice has mo ed appreciably. The advantage over the arrangement of Figure 1 of this apparatus for scan file generation is twofold; firstly any eπors in inertial navigauon signals between stπpes are eliminated, and secondly that data density of acquisitions within the scanned t o dimensional area on the surface of the object will be much more linear, and totally independent of swiping speed. The term 'effecϋvely instantaneous' acquisition of data is used to descπbe an acquisition of many surface points m a two dimensional matπx or raster projected onto the surface of the object in a peπod which is so short that the maximum movement expected of the scanning device 10 in this time will be less than the required accuracy of the surface profile data. For example, if the maximum swiping velocity expected is 250 mm/s and the required accuracy is 1mm, then at the maximum velocity , it will take : 1/250 = 0.004s. Thus in 4ms an entire two dimensional acquisiϋon must be performed. Preferably, each acquisition w ill contain at least several hundred points. For example it each scan of polygonal mirror 40 results in the acquisition of an array of 32 by 32 points on the surface of the object, this will require 1,024/0.004 = 256,000 points to be acquired per second. Besides the rotating polygon scanning arrangement descπbed above, several possible scanmng technologies are known which can currently meet this specification, including acousto-optic deflector and electro-optic deflector systems, w hich may optionally be combined with a resonant line scanner. All of these systems are capable of projecting a spot onto the surface at a vaπable angle to the scanmng dev ice in two dimensions, and can control the angle of projecUon at high speed. In particular, acousto-optic deflectors can currently be obtained to alter the refractive index of a crystal to divert the beam in any one of up to 1000 linearly spaced unique angles. Certain acousto-optic devices may be coupled to provide XY random access deflection. The rotating polygonal mirror system descπbed above requires a medium-speed rotating poly gonal mirror 40 to provide the line scan in each line of the raster, and a low -speed scanner such as a further rotaϋng poygonal mirror in optical arrangement 300 to prov ide the ertical raster movement reposiuoning the start of each line. At a rotation speed of 20,000 r.p.m., polygonal mirror 40 provides a scan rate of 8,000 lines/sec if a 24 facet polygon is used ( 15 degree angle of scan), and scans 32 lines in 4ms. The further rotating polygonal mirror of optical arrangement 300 may be a 24-facet polygon rotating at ( l/0.004)/24x60 = 625RPM i.e. scanmng once every 4 milliseconds. As noted above, the preferred photodetector 34' is a lateral effect two dimensional linear silicon photodetector which generates an output indicating the offset of the centroid of the incident light relative to the centre of the photodetector in conunuous analogue form. Such photodetectors are capable of resolving optical changes at sev eral MHz. The processor 42 in the embodiment of Figure 3 preferably includes high speed flash analogue-to-digital converters which digitise the X and Y centroid signals from the photodetector which correspond to the surface profile at specific angle of projection of beam 3' at that point at the time of measurement. The digitised points are then converted to points in a three-dimensional coordinate system which is common to the entire scan performed by polygonal mirror 40 with the aid of signals from sensor 41 , which may be a Hall effect sensor for example. These signals indicate the instantaneous onentation of beam 3'. If an acousto-optic device is used for scanmng, the required information on the beam oπentaϋon can be deπved from the dnve signals to the device. Much more data can be captured by using the arrangement of Figure 3 than by using the arrangement of Figure 1, and as the movement between scan files can be very small, each successive scan file can contain a very high proportion (e.g. 507c or more) of the data in the preceding scan, thus making overlapping almost complete. This enables the surface portions corresponding to successive scan files to be combined relatively easily to obtain a complete surface descπption of the object 1. In particular, although the arrangement of Figure 3 is shown with an accelerometer 50 and a g roscope 51 which are similar to the acclerometer and gyroscope of Figure 1, it is not essential for the output of processor 42 to be combined with data deπved from such an accelerometer and a gyroscope in order to give a succession of scan files including the required position and attitude data as generated by circuitry 25 in Figure 1. Instead the scanned surface portions can be combined by a computer w ithout the assistance of such data, as will become apparent from the subsequent descπption However the signals from the accelerometer and gyroscope can be used a) to deπve the change in posiUon and attitude of the scanning device between successive scan files so that successive pairs (or larger groups) of scan files can be combined to form composite scan files which require less processing to be fitted together to form the complete surface descπption and b) to provide posi on and attitude signals to the subsequent processing circuitry which indicate to that circuitry w here regions of overlap between successive scan files may be found, thereby simpifying processing. The use of such signals w ill be descπbed subsequently ith reference to Figure 5. Turning now to Figure 4, which illustrates the processes and dataflows earned out on the scan files by computer 47, the coordinate data of each scan file (numbered 1 to N) are represented as clouds of points 611 to 61^- The follo ing sections detail the data and processes descπbed in the diagram. Data : scan file of raw 3D coordinate data This is a file of data captured from a single scan of the scanning dev ice 10 (represented as a CLOUD OF POINTS) It will contain a vanable number of acquisitions ot surface profile 3D co-ordinates. When the scanmng dev ice tπgger s itch T is pressed, and the speed in any direction exceeds a starting threshold, then a scan commences When the tπgger switch T is released, or the speed in any direction falls below a second (lower) threshold (for hysteresis), the scan is terminated. Dunng this peπod, profile acquisitions are made at regular time inter als, and thus the number of profiles is directly proportional to the duration of the scan. Each profile acquisition will contain a number of distance samples along the length of the profile. In addition to the basic 3D coordinate data, a number ol extra data items may be included in each scan file in order to assist vaπous subsequent processes in performing error correction such as a scan file time stamp to indicate the time of the start of the scan, scanning dev ice position and attitude, and surface colour in another embodiment. Process 62 . scan file surface fit The scan file consists of essentially a set of randomly placed and unassociated points on w hich any further processing is extremely difficult as the points are unordered and in an unsuitable formal for later post processing stages. This process fits a mathematical model to the surface desenbed by the randomly ordered points in the scan file w hich is in a form suitable for later post processing operations It should be noted that this mathematical model is not necessaπly an expression for the surface in terms of x,y and z coordinates but is merely an ordered form of the raw data w hich enables features of interest such as discontinuities to be extracted in subsequent processes. This has two effects: ordeπng the data to a know n format, and production of a complete surface model of the scanned area regardless of v arying data density. It must be noted though, that some data is lost in this process, as the model of the surface does not retain the oπginal raw coordinate data. There are vaπous methods of producing a surface descπption of a set of unordered 3D co-ordinates, including l) k- d binary trees, n) local neighbourhood region growth algoπthms, and in) Delaunay Tπangulation of Voronoi diagrams. l) Th k-d Binary Tree The k-d binary tree (Henderson 1983, Fπedman et al 1977) positions the data on a binary tree in w hich each point on the tree is connected to its nearest neighbours Thus subsequent surface feature detection is made possible by examination of each point in turn and its spatial relationship to its nearest neighbours π) Local Neighbourhood Growth Algoπthms The local neighbourhood growth algoπthms operate by selecting one or more seed points (usually at discontinuities) and growing the points into regions (influenced by the unstructured point data) until the regions meet and completely descπbe the set ot unstructured points in a spatially coherent manner suitable for further processing. Grow th of a region is prevented at a discontinuity (such as an edge for example) and hence this method has the advantage of automatically detecting discontinuities dunng the process, thus making the identification of points of interest in later processing much simpler. It has the disadvantage of requiπng more processing than either of the other t o methods descπbed here. in) Delaunay Tπangulation of Voronoi Diagram In the Delaunay Tπangulation of Voronoi diagram (Toussamt 1979), a Voronoi diagram is built up by defining a plane associated with each detected surface point such that each point within that plane is nearer to that detected surface point than to any of the other detected surface points. Thus a polyhedron is built up w hosepolygonal faces are centred on respective detected surface points, the edges of the polygonal faces being midway between neighbouπng detected surface points. The resulting partial polyhedron is then simplified by defining a tπangular face between three detected surface points and measuπng the perpendicular distance between it and the intermediate detected surface points lying above it. Depending on the magnitude of this distance, the tnangle is either split into two mangles defined by these points as vertices or the points are eliminated The resulting descπption of the scanned object (a part of a polyhedron having tπangular faces) is concise because extra tπangles are only formed where the previous approximating surface was not satisfactory . Francis et al 1985 descπbe a similar method but for v ery large data sets. The data resulting from process 62 will be a surface model in a form suitable for the extraction of points of interest. This surface model can be in the form of a set of splines, a binary tree, or a set of connected tπangles or other polygons depending on the precise method used in process 62. Process 63: detection of "points of interest" These can be defined as points at which any deπvative of the local surface (particularly the gradient i.e. the first deπvative) passes through zero and include edges, comers, peaks, troughs and saddle regions. The methods for detecting these features include i) plane slicing and n) surface curvature analysis. In some instances where surfaces are essentially featureless, small and easily removable markers of known shape and size may be placed on the object to be scanned in order to generate artificial "points of interest". These may be removed from the scan file at the end of the processing by a process of subtracting the appropnate 3-D model. i) Plane Slicing Conceptually, the process of plane slicing involves taking successive plane slices at regular intervals along an axis that traverses the approximate centre of the scan data. This w ill prov ide a set of contour maps, of the surface at successive depths into the range data. By interpreting the difference between the data in any given plane slice and its preceding and following planes features such as corners and edges may be detected. This process can be iterative, in that initially a coarse spacing between planes can be used, followed by successively finer spacing between planes until points of interest are identified. li) Surface Curvature Analysis With spline or polygon descπptions of the surface form as the input data, surface curvature can be used to find discontinuities in a surface by detecting points with diverging splines. This method can also be used to detect surface features that w ill not be detected by other means, in that a smooth parabolic surface can be completely descπbed mathematically, and used as a point of interest (its gradient passes through zero) for scan registration rather than surface point features as in the other methods. For this reason, this method is important as a tool to a genenc surface integration package, as it w ill allow the registration of scan files w hich contain few if anv discontinuities. Besl et al IEEE Trans PAM1 Vol 10 No 2 pp 167 -192, March 1988 (incorporated herein by reference) descπbes a method of surface feature recognition using surface:rwo viewpoint invariant curv ature etπcs, namely Gaussian Curvature (K) and mean curvature (H). There are eight possible combinations of polaπty of these parameters corresponding to eight possible surface types, namely peak, πdge, saddle πdge, fiat, minimal surface, pit, alley, and saddle valley. The data flow from process 63 compπses "points of interest" associated with each scan file and can be represented by a list (e.g. peak, saddle, saddle, trough) linked to a further list of spaUal relationships between each of the points of interest. Each point of interest in the first list can be descπbed by the following set of data or some subset: - Coordinates of the centre of the point of interest in the local co-ordinate reference frame for that scan. - Relative Acquisition angle of scanning device to point of interest in the local co¬ ordinate reference frame tor the scan. - Type such as Peak, Trough, Pit, Saddle etc. - Magnitude of the discontinuity causing the point of interest. - Surface Characteπstics e.g. colour, reflectivity (assuming that a photodetector responsive to such characteπstics is used and that the relevant data is available). Process 64: Common Feature Detector By matching the set of points of interest and their spatial relationships in each scan file w ith the respective sets of points of interest of other scan files, surface features which are common to different scan files are identified. This technique is descnbed in Soucy et al IEEE Trans. Pattern Analysis and Machine Intelligence 17 No. 4 Apπl 1995 w hich is incorporated herein by reference. In particular, for each pair of scan files, a search is performed for similar point of interest types, resulung in a list of common point of interest types between the pair of scan files. Subsequently, the relative spatial relationships between the common points of interest in the list for each scan can be compared by first matching distances between pairs of similar types to produce a subset of the onginal list where the spatial relationship between pairs of points of interests is matched. The relative spatial relationship of other neighbouπng points of interest to the matching pair from each scan is then checked for a match containing three points of interest to produce a subset of the matching tπplets of points of interest. This is the minimal requirement for determining that any set of features are common between scans. The process is continued until no further matches are found. The larger the number of matched points of interest, the greater the confidence in a correct matching between o erlapping surface features between scans. An example of such a process is as follows: peak peak peak πdge πdge saddle pit minimal surface Firstly the features not common to scan files 1 and 2 (namely the saddle and minimal surface) are eliminated from the compaπson. Secondly the distances between each pair of features in scan file 1 are calculated and a coπesponding calculation is made of the distances between each pair ot features in scan file 2, resulting in the follow ing lists: Scan file 1 Scan file 2 Each distance in scan file 1 is compared with corresponding distances (i.e. distances between corresponding groups of features, e.g. peak-ndge) in scan file 2. It may be found that peak-πdge distance a of scan file 1 matches the peak πdge distance of scan file 2, that the peak-pit distances a of the respective scan files match and that the πdge-pit distance of scan file 1 matches the πdge-pit distance a of scan file 2, for example. These matching distances are then processed to find the list of sets of three distances between the possible combinations of the three different features. The resulung lists in this case each compπse one set of distances between a peak, a πdge and a pit: Scan file 1 peak-πdge distance, peak-pit distance, πdge-pit distance Scan file 2 peak-πdge distance, peak-pit distance, πdge-pit distance If these sets of distances match, then the peak, πdge and pit are assumed to be common to scan files 1 and 2. For all scan files in which a minimum of three points of interest have been matched to another scan file in this manner, the three rotations (about the x, y and z axes of the coordinate system of one scan file) and the three translations (along those x, y, and z axes) required to supenmpose the common points of interest of one scan file onto another are determined. The abov e three rotations and translations are output from process 64 to process 65, in respect of each pair of scan files having common features (areas of overlap). Process 65: scan file rotation & translation The abov e rotations and translations are applied to the clouds of points of all the ov erlapping scan files, resulting in a single cloud of points defining the enure surface 3 of the scanned object relative to an arbitrary coordinate system. Alternatively these rotations and translations may be applied to surface models generated in step 62. 10 The resulting data is of an identical type to the oπginal scan file cloud of points or surface model, but translated to the common coordinate system. Process 66: Non-Redundant Surface Model Generator 15 There are three basic methods of surface integration of a set of multiple ranged images into a single non-redundant file, any one of which can be selected for use in this process: 20 1.) Directly calculating surface models on sets of unorganised 3D points These techniques have the advantage of being able to calculate a surface model with only point data. They make the assumption that: _3 a. the N nearest surface neighbours of point p can be estimated from its n nearest 3D neighbours, b. data density is relatively uniform over the surface of the object to be modelled, c. points are measured with the same accuracy 30 Such techniques have problems at large surface discontinuities unless the sampling density is high, and when data is of diffeπng accuracy ( e.g. when data is obtained from reflections at acute angles to the surface). An example of such a method is 5 Hoppe's algonthm ( H. Hoppe et al, Proc. of SIG-GRAPH'92, pp 71-78, 1992 hich is incorporated herein by reference). 2. ) Producing a surface model assuming parametπc surface descπptions for each of the scan files. 40 This method y ields a more accurate surface model than 1.) when the registration error is small compared to the data acquisition error. For successful modelling using this technique, the object cannot have a hole, and the projection of the cy ndπcal or 45 spheπcal gπd on the surface of the object must be continuous. 3.) Estimating a surface model piecewise using Venn diagram of the set of scan files. This method places no restπctions on the topology of the object to be modelled and is 50 the single most useful method, although all three methods are available w ithin process 66 and can be selected by the user by enteπng appropnate commands at the keyboard 130 of the computer 47 (Fig. 2). The method is described in section III (p 346 et seq) of Soucy et al IEEE Trans ^ Pattern Analysis and Machine Intelligence (supra) and is summaπsed below . Before combining the scan files, they are preprocessed in four steps; a. Remove data below an accuracy threshold. b. Remove data outside a depth w indow. c. Detect range discontinuities by thresholding the 3D distance between hoπzontal and vertical neighbours m the raw scan files. d. Project raw scan file onto a plane and parametπse using a square gπd topology. In the resultant files ot point coordinates (w hich are reteπed to below as range iew s), the parametπc distances between two consecutiv e v ertical points, and two consecutive hoπzontal points are equal. 10 The Venn diagram is obtained by calculating the common surface segments bet een all possible pairs of range view s. Each area of overlap of surface features between two or more range views becomes a canonical subset of the Venn diagram. The procedure to obtain the Venn diagram from the set of range views consists of finding 15 the intersections between all possible pairs of range views, and once computed, it is possible to determine for each point in each view, w hich other v iew s hav e sampled an element on the surface at that point. The contents of the canonical subsets of the Venn diagram are thus implicitly available. 20 Giv en that the point data will by noisy and have finite resolution, in order to determine w hether a point in one range view matches a point in another iew , two tests have to be performed, the Spaϋal Neighbourhood Test and the Surface Visibility Test. These tests must be performed on all surface points in both range v lews. 25 The Spatial Neighbourhood Test (SNT) is used to check whether the Euclidian distance between a point in one view, and a surface patch in another view is small enough in relation to the measurement error to determine that they belong to the same 30 3D neighbourhood. The definiUon of the surface patch is local and is defined as the plane formed by the three nearest neighbours of the point once transformed in the parametπc gπd of the other view. The Surface Visibility Test (SVT) tests whether a patch in one v iew is visible to a 35 patch in the other v iew by considenng local surface onentauon information. For example if two range v iews have respective sets of points with similar coordinates w hich therefore satisfy the Spatial Neighbourhood Test (SNT = TRUE), these sets of points might nevertheless belong to different surfaces, such as the inside and outside surface of a thin shell for example. The SVT cπteπon involves the determination of 0 the angle between the normals to the surfaces corresponding to the sets of points; only if this angle is less than 90 degrees is the cπteπon satisfied (SVT = TRUE). Points for which SNT = TRUE and SVT = TRUE are, to a first approximation, the 4 5 points w hich are common to different range views. However the above estimates are not complete estimates of the canonical subsets (i.e. common points) because the above tests are unreliable near step disconαnuities such as edges and corners for example. 5 Accordingly these initial estimates are used as seeds to an iterative region growing process that expands the seeds until they reach the boundaπes marked by contours of steep discontinuity pixels. A consistency cπteπon must also be imposed to prev ent an isolated point from growing freely. This cπteπon can be defined as at least fifty .. per cent of elements in an expanded region must be SNT and SVT TRUE The region ^ grow mg algonthm relies on a modified 8-neιghbour blob colouπng algonthm. Instead of checking w hether tw o 8-connected pixels in a given view share the same property or not, it checks to see if they are disconnected by a contour of step continuity pixels 4-connected to elements of a seed region in either of the vie s. When extracting the non redundant model from the Venn diagram, first a set of tnangulations modelling each canonical subset of the Venn diagram is calculated. These local tnangulations are then combined to yield a complete integrated tnangulation modelling the object. The resulting model, in a custom format, is output from process 66 to process 67. Process 67 : file format conversion The complete integrated tπangulaϋon model is used as the input data to a file format converter to produce a file descnbmg the object in a standard file format suitable for display , manipulaϋon and storage by a large number of 3D software packages including but not limited to CAD on a wide vaπety of platforms. Data : Object Descπption in industry standard file format Common 3D file formats which can be supported by the file format conversion utility include: Bezier Curves, B-Spline Curves and Surfaces, B-Rep models, Constructiv e Solid Geometry (CSG) & CSG Tree, DXF geometry Exchange Format, Initial Graphics Exchange Standard (IGES) (and vaπants - VDA-IS / VDA-FS), Non Uniform Rauonal B-Sphnes (NURBS), Octree Model, and Step/Pdes. This data is output to a CAD software package 68. Some or all of the above processes may be displayed on the computer ' s display 131, particularly the rotauons and translations needed to fit together the surface portions, which may be corrected or adjusted by the user. The computer 47 is suitably a graphics workstation or may be a high speed personal computer. Turning now to Figure 5, an object 1' (a paper cup) is shown being scanned by a scanning device 10, which is assumed to incorporate the preferred optical arrangement and accelerometer and gyroscope of Figure 3. The comers of the first scan (i.e. that area covered by one hoπzontal sweep of beam 3' due to the rotation of the polygonal mirror 40) over the surface of the object are indicated at p,q,r, and s and it will be noted that this overlaps substantially with the next scan t,u,v,w. Below these two scans, a second row of tw o further scans are shown on the surface of the cup and the operator holding the scanning device 10 ensures that the two rows overlap. As already noted in connection with the descπption of Figure 3, the overlap between successive scans pqrs and tuvw is due to the rapid scanning rate of poly gonal mirror 40 in relation to the rate at which the projected beam from the scanmng dev ice is swept across the surface of the scanned object 1 ' . Accordingly it is inevitable that the edge region of each scan (e.g. the region of scan pqrs shown hatched) will overlap the edge region of the next scan. For example, the edge region between comers r and of the first scan shown in Figure 5 will overlap the edge region between comers t and u of the second scan. Accordingly, COMMON FEATURE DETECTOR process 64 in Figure 4 can be guided to look in the edge region of each scan file for overlap, preferably in real time as the scan files are generated by scanning device 10. In other words, instead of waiting until all of the scan files have been generated and then looking for overlap between ever possible pair of scan files, the process 64 can look for overlap between regions (particularly edge regions) of successively generated scan files. Furthermore it w ill be apparent that if inertial sensing means such as accelerometer 50 and gyroscope 51 are earned by scanmng device 10, the outputs of such inertial sensing means can be processed to determine the velocity and direction of movement of the scans over the surface of the object 1 ' and hence to predict the precise regions of ov erlap of successive scan files. Even if the inertial sensing means is omitted, the v elocity and/or direction of movement between the first two scans can be deπv ed from the location of the common features in their scan files and can be used to predict, to a first approximation, the reeion in which the next two scans will ov erlap, so that COMMON FEATURE DETECTOR process 64 will look only in this region for common features. In these embodiments the processing needed to idenufy common points in successive scan files is much reduced and should be easily achiev able in real time. It may be desirable to re-set the accelerometer and gyroscope dunng the scanmng and for th s purpose a docking station 100 is provided, to which the scanning device may be returned peπodically dunng scanmng. If each sweep is begun by taking the scanning device from the docking station, the accumulated errors from the accelerometer and gyroscope can be reduced. Furthermore a reference object 200 of known size and shape may be scanned before the object 1 ' is scanned and used to calibrate the system. In pπnciple a file defining the entire surface of object 1' could be built up, provided that the object is kept in view by the photodetector 34' of the scanning device 10 throughout whilst sweeping the entire surface of the object with the projected pattern from the scanning device. However this may not always be practicable and in general it may be easier to combine successive scan files defining part of the surface of the object to form a composite scan file, to repeat this process to form further composite scan files, and then to combine the composite scan files at the end of the scanning process by means of processes 64 and 65 of Figure 4 to form a complete surface descπplion. Furthermore the SURFACE FIT process 62 of Figure 4 can be simplified if the coordinate data of all the points is read out from the processor 47 (Figure 3) in seπal fashion in a predetermined order (such as the order of acquisition for example) or in some other manner w hich preserves the information on their location within the scan. The nearest neighbours of each point can be identified from such information w ithout requiπng the calculation of the distances between all pairs of points, and hence a surface can be built up by joining each point to its nearest neighbours. Assuming that the angle of sweep of beam 3' in the scanmng arrangement of Figure 4 is relatively small, the resulung surface will approximate to a projection on a rectangular gπd. Accordingly it will be apparent that many of the the somewhat complex procedures for finding common features of scanned surface portions as descπbed above with reference To Figure 4 can be dispensed with if the preferred scanning arrangement of Figure 3 is employed. Furthermore performance advantages may be obtainable by using gene c algonthm techniques (as descπbed in "Advances in Genetic Programming by K.E. Kinnear and "Genetic Programming II: Automatic Discovery of Re-usable Programs" by John R. oza, Department of Computer Science, Stanford University, Stanford, California 94305, incorporated herein by reference) or the related technique of Boltzmann simulated annealing. In both cases, a random factor is introduced into the postprocessing algorithms with the results measured using fitness cπteπa such as, for example, closest approximation of points of interest (in large data sets) common to successive range data files, with subsequent selection of those progeny algoπthms producing the best fit, over multiple iterations. A similar method for reoπentation and registration of data files in 6 dimensional space may be deπved easily from the techniques descπbed in Report No. STAN-CS-TR-95- 1535 Thesis: Random Networks tn Configuration Space for Fast Path Planning', December 1994 by Lydia E. avrak , Department of Computer Science, Stanford University, Stanford, California 94305, which is also incorporated herein by reference. In this connection, reference is made to Figure 6 which shows two surfaces SI and S2 in the form of projections on a rectangular gπd which have been deπved from successive scan files output from the scanning arrangement of Figure 4. The normals N defined by (say) the four adjacent points of one surface S2 are calculated at least for the overlapping edge portions of the surface and then a) the distance along each normal at which it cuts surface S2 is calculated and b) the three rotations and translations needed to minimise the sum of these distances of mtersecuon (corresponding to the best overlap) is determined by the genetic or other iterative algonthm. Such a technique does not require the detection of discontinuities or other "points of interest". A further embodiment of the present invention could provide simultaneous capture of a colour and texture overlay with surface posiuon data, by the use of a colour CCD or similar two dimensional colour photodetector device instead of, or in addition to, the present photodetector, while strobing the laser or using a broadband light source. A still further embodiment of the present invention may retain the inertial position and attitude measurement system as described in connection with Figures 1 and 2 but may use any other means for determining the surface coordinates relative to the scanning device. In a still further embodiment of the present invention the position and atutude measurement system may be mounted on the object to be measured and the object can be moved around the fixed scanning device, or a further position and attitude measurement system may be provided on the object being scanned in addition to that on the scanning device, enabling both the scanned object and the scanning device to be moved freely. Furthermore it is not essential to process the scan files to compare overlapping surface in order to register the detected surface portions of the scanned object. Instead, the required rotations and translations could be deπved entirely from the outputs of the inertial sensing means if the inertial sensing means is sufficiently accurate. The laser 28 used as the light source may be replaced by a light-emitting diode and other wavelengths besides opucal wavelengths can be used, particularly I.R. wavelengths. Accordingly the term "optical" is to be construed broadly to include any radiation or arrangement which obeys the laws of optics. A still further embodiment of the present invention could utilise a controllable lens system with vaπable magnification in order to prov ide increased dynamic range of depth measurement. A still further embodiment of the present inv ention could include a density , mass and v olume calculator in the computer (47). If the surface of the scanned object is highly reflective or highly transparent, the application ot inert fine powder, for example fingerpπnting dust, may be helpful.

Claims: Claims 1 A scanning arrangement tor determining the shape or other three-dimensional 5 surface characteπstics ot an object ( 1 ), the aπangement compnsing a scanning dev ice ( 10) w hich is f reely mov able relative to said object, the dev ice composing " a) an optical projector (5) for projecung a predetermined pattern onto a region ' of the surface (2) ol the object, and b) an optical detector (6) for detecting the coordinates or other surface 1 characteπstics of said region and for generaϋng output signals representativ e of such coordinates or other surface charactenstics, the aπangement lurther including 1 c) processing means (25,26,27) coupled to said detector for generating a set of output data representing said surface characteπstics of a scanned portion (pqrs, tuv w ) of the surface of said object, d) combining means (47) coupled to said processing means for combining sets of such output data deπved from overlapping scans ot said surface into a common set 2 0 of output data by appropnate rotations and translations, said combining means optionally including further processing means (61-66) lor calculating said rotations and translations from subsets ot respective sets ot such output data hich relate to a common area of said surface, e) optionally, inertial sensing means (50,51) for detecting mov ement of said 2 5 scanning de ice relative to said object and generating output signals representaϋv e of such movement, and 1 ) coπecting means (23,47,50,51 ) for coπectmg for mov ement of said scanning dev ice relative to said object between successive scans, 3 0 said correcting means being responsive to at least one of l) output signals from said inertial sensing means (if present) li) output data from said further processing means (it present), the arrangement including either said inertial sensing means or said further ^ 5 processing means or both. 2 A scanning aπangement according to claim 1 w herein said combining means ( 47) compnses a) means for recognising features of said object common to ov erlappine scans, and b) means for translating said sets of output data to a common coordinate system in w hich a feature as detected in one scan is supeπmposed on that feature as detected in an overlapping scan 3 A scanning arrangement according to claim 1 or claim 2 wherein said posiUon- 5 sensing means compnses a) inertial sensing means (50) earned by said scanning device ( 10) for generating acceleration data indicative of the linear " acceleration of said scanning dev ice. and b) integrating means (23) responsive to said acceleration data for determining changes in linear position of said scanning dev ice between successive scans 4 A scanning arrangement according to claim 3 w herein said inertial sensing means (50) is coupled to means for inhibiting the acquisition or processing of said output data v hen the detected acceleration is outside a predetermined range. 60 5 A scanning arrangement according to any preceding claim wherein said position - sensing means compnses inertial sensing means (51) earned by said scanning dev ice tor determining the rotation of said scanning device between successiv e scans 6 A scanning arrangement according to claim 5 wherein said inertial sensing means (51) is coupled to means for inhibiting the acquisition or processing of said output data when the detected rate of rotation is outside a predetermined range. 7 A scanning arrangement according to any of claims 3 to 6 w herein said inertial sensing means (50,5l) is responsive to changes in posiuon and/or attitude of said scanmng device ( 10) dunng each scan and is arranged to correct each set of output data for such changes in position and/or attitude dunng each scan. 8. A scanmng arrangement according to any of claims 3 to 7, further compπsing means (25) for associating the detected surface coordinates of said region witn attitude and/or posiUon data descπbing the attitude and/or position of said scanmng device ( 10) relanve to said object ( 1 ) at the time of optical detection of said coordinates. 9. A scanning arrangement according to any preceding claim wherein said scanning dev ice ( 10) carnes multiple inertial sensing means (50,51) for determining changes in position of said scanmng device along three mutually perpendicular axes and changes in onentauon of said scanmng device about three mutually perpendicular axes. 10. A scanning aπangement according to any preceding claim wherein said optical detector (6) compnses: a) a detector (34) sensitive to the two-dimensional position of said pattern, and b) imaging means (33) for forming on said detector an image of the intersection of said pattern with said region. 1 1. A scanmng arrangement according to claim 10 wherein said opucal projector (5) includes means (29,30) for projecting a line of optical radiaUon onto said region and is spaced apart from said detector (6) alone a first axis, said line of optical radiation being substanually perpendicular to saiα first axis. 12. A scanning arrangement according to claim 10 wherein said optical projector (5) includes means for projecung a two-dimensional pattern of optical radiation onto said region. 13 A scanmng arrangement according to any of claims 10 to 12 wherein said optical detector (6) compnses scanmng means (40) for scanmng said optical pattern relative to said scanmng device (10). 14. A scanmng arrangement according to any of claims 10 to 13 wherein said optical projector (5) compnses a scanmng arrangement (300) which generates said optical pattern by scanmng a beam in at least one direction relative to said scanmng device (10). 15. A scanmng arrangement according to any of claims 10 to 14 wherein said detector (34) is inclined with respect to the opϋc axis of said imaging means (33). 16. A scanning arrangement according to any preceding claim wherein said optical detector (6) is sensitive to the colour of the surface (2) of said object ( 1) ana said output data includes data representative of said colour. 17. A scanning arrangement according to any preceding claim which is coupled to a display for displaying the surface defined by ' the combined output data. 18. A scanning arrangement according any preceding claim which is coupled to manual input means for selectively controlling the combination of different scanned surface portions of the object ( 1 ). 19. A scanning arrangement according to any preceding claim w herein said combining means (47) compnses a microprocessor (46) programmed to output coordinate data of said object in a standard file format. 20. A scanning arrangement according to any preceding claim w herein said scanning dev ice ( 10) includes a manually operable switch (T) for inhibiting the acquisition or processing of said output data. 21 A scanning arrangement according to any of claims 3 to 9 w herein a fixed docking station ( 100) is prov ided for said scanning dev ice ( 10) and said inertial sensing means is responsive to the docking of said scanning dev ice at said docking station " to re-set said correcting means (23,47,50,51). 22. A method of determining the shape or other three-dimensional surface characteπstics of an object ( 1) by means of a scanning device ( 10) w hich is freely movable with respect to the object, the method compπsing: l) projecting from the scanning dev ice a predetermined optical pattern onto a region of the surface of the object, li) optically detecting the coordinates or other surface characteπstics of said region with an optical detector (6) mounted on said scanning device, in) denving a set of output data representing said coordinates or other surface characteπstics of said region, iv ) repeatedly scanning said optical pattern over said object in overlapping fashion and denving further sets of output data from overlapping scans, and v) correcting said sets of output data for movement of said scanning dev ice relative to said object between successive scans either by sensing movement of said scanning device relative to said object with an inertial sensing means (50, 51) or by determining the rotations and/or translations needed to supeπmpose subsets of respective sets of said output data which relate to an area of said surface which is common to said sets. according to claim 22 w herein said scanning device ( 10) 24. A method according to claim 22 or claim 23 wherein said rotations and/or translations are determined between successively acquired sets of output data. 25. A method according to any of claims 22 to 24 w herein predetermined regions of said overlapping scans are processed to determine regions of overlap. 26. A method according to claim 25 wherein said predetermined regions are determined from data indicative of the velocity and/or direction of movement of the optical pattern over the surface of the object ( 1). 27. A method according to any of claims 22 to 26 wherein an iterative algonthm is used to determine said rotations and/or translations. 28. A method according to any of claims 22 to 27 herein normals (N) to scanned surface regions (SI ) are generated and the distances along these normals at w hich thev intersect other surface regions (S2) are determined under different rotations and translations. 29. A method according to any of claims 22 to 27 wherein groups of surface features of respectiv e scans are identified and compared in order to determine said rotations and/or translations. T) 0 A method according to any of claims 20 to 29 wherein said scanning device is calibrated by scanning an object of known shape.

Inventors: FLOCKHART CHRISTOPHER PETER, FOWLER GUY RICHARD JOHN, FLOCKHART, CHRISTOPHER, PETER, FOWLER, GUY, RICHARD, JOHN
Applicants: FLOCKHART CHRISTOPHER PETER, FOWLER GUY RICHARD JOHN, FLOCKHART, CHRISTOPHER, PETER, FOWLER, GUY, RICHARD, JOHN
Application year: 1995
Main classification: G01B11
IPC codes: G01B11, G01C3, G01C19, G01P15, G01S17