3D inspection system for manufactured machine parts

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1 3D inspection system fo manufactued machine pats D. Gacía a*, J. M. Sebastián a*, F. M. Sánchez a*, L. M. Jiménez b*, J. M. González a* a Dept. of System Engineeing and Automatic Contol. Polytechnic Univesity of Madid. Spain b Dept. of Expeimental Scienc * es and Technology. Miguel Henandez Univesity. Elche, Spain. ABSTRACT This pape pesents a new system fo inspecting 3D manufactued machine pats with high accuacy. The system focuses on two main aspects: a definition of specific tools fo inspection and 3D measuement and high flexibility fo featue selection. As a esult, a novel system fo inspecting objects with 3D chaacteistics has been developed. The input infomation is a complete knowledge of the inspection wokbench setting (elements, chaacteistics and esolution anges) and a CAD model of the pat to be inspected. Using an inteactive inteface, the use may define the featues to inspect and the pecision equied fo each one. Some of the opeations the system pefoms ae dimensional contol with subpixel accuacy, suface inspection and object edge finish. Based on the CAD model and the featues to inspect the system automatically designs an inspection planning esponsible fo managing the diffeent esouces involved in the inspection pocess. Povided that the aim of the system is to obtain the geatest possible accuacy, a geat effot has been done in the aea of mechanical devices and camea calibation. Also, in ode to quantify the goodness of the esults obtained, an uncetainty popagation stategy has been caied out thoughout the measuement pocess. Keywods: Inspection, 3D, calibation, planning, quality contol 1. INTRODUCTION Inspection of thee dimensional machine pats is of fundamental impotance in industial manufactuing. It is woth mentioning some efeences that descibe the state of the at in this field 1. Among the diffeent systems developed, those that utilize non-visual techniques ae the most numeous 3,4,2. Thee ae a geat vaiety of these non-visual techniques although the vast majoity of applications make use of coodinate measuing machines (CMM) due to the possibility of integating them in an automated measuement cell. These machines povide thee-dimensional measuements fom the position of its contact pobe. Taditionally, CMM have been used in the field of quality contol. Recent impovements of communication intefaces allow one to tansmit a CAD model of the machine pat to be inspected so inspection may be pefomed in a moe effective way. On the othe hand, thee is a gowing tendency fo integating non-contact sensos, such as cameas and lase devices, into measuement cells. An inteesting example of such systems may be found at 5. In this application, a vision system calculates a fist estimation of measuement while CMM povide accuacy. This vey same system may be used fo evese engineeing tasks. Of late, howeve, non-contact inspection methods 6,7,8 ae becoming an attactive altenative to the systems pesented in the pevious paagaph. Some of these systems have been developed in the field of close-ange photogammety 2, making use of vaious methods such as theodolites, film-based cameas o, moe ecently, CCD cameas. This kind of systems has been fully exploited fo the automobile and aeospace industy. Photogammetic systems ely on detecting cetain contol points (typically eto-eflective tagets) by means of techniques such us centoiding and template matching. Usually, these systems ae configues in one of two ways: a) as single sensos off-line systems o b) as multi-senso eal time measuement systems 18. Close to these systems, automated visual inspection systems have been attacting wide usage ove the past few yeas. These systems have cetain advantages such as flexibility, velocity, automatic pose detection and a geate poductivity. Howeve, thee ae two citical disadvantages that educe geatly its applicability. In the fist place, lack of access that limits the * Coespondence: dgacia@disam.upm.es, jsebas@disam.upm.es, fsanchez@disam.upm.es, luis.jimenez@umh.es, jgonzale@disam.upm.es; WWW:

2 complexity of the elements to be analyzed. Secondly and moe impotant, lack of esolution (pecision). This point is the key facto fo measuement applications. Ou wok may be placed in this field. One of the difficulties fo impoving pecision is hadwae esolution, especially CCD esolution 15. Nevetheless, it is not the only eason fo this lack of pecision. An inadequate use of physical devices and a bad teatment of data may lead to a continuous loss of pecision at evey stage of inspection. In this sense, the system pesented povides a flexible envionment fo inspection and intends to go deeply in eo analysis so that the use of diffeent esouces is optimized and maximum potential esolution is eached. On the othe hand, the system is designed towads obtaining a pecise measuement of those dimensions citical fo the opeation of the pat. Such dimensions may be epesented by means of high level basic geometic entities. Theefoe, analysis of a model consists in seaching fo the state of the system in which each entity is inspected in the best possible way, as opposed to the est of the machine pat elements that may intefee with inspection. This stategy allows one to develop inspection planning in a vey natual way due to the fact that these basic entities detemine by themselves the most effective methodology to be followed. The contents of this pape ae explained as follows. In the fist place, the aim of ou system (fom now on called DISAM inspection system), the chaacteistics of this kind of applications and the special featues of ou inspection system ae evised. Next, the diffeent aspects on which the system is based ae descibed in detail. These ae pecision, calibation, geometic entities and planning stategy. Finally, conclusions obtained and futue impovements ae pesented. The aims of ou system ae detailed as follows: 2. GENERAL APPROACH The system pefoms dimensional contol on manufactued machine pats. These pats have well defined theedimensional chaacteistics. The key facto to seach fo is accuacy. Inspection is based on an ideal CAD model of the pat and a detailed specification list. This list clealy defines the elements to inspect and its toleances. Initial pose of the pat is known. Once the pat has been moved in space, its new position is checked in ode to assue accuacy. The system must have a fiendly use inteface and easiness of use. When the system pefoms thee-dimensional inspection two diffeent opeations may be caied on. Fist of all, shape analysis o dimensional measuement of a single featue and second, analysis between two diffeent featues. The matte of pefoming one of these two opeations comes as a esult of the inspection task being pefomed 20. The vaiety of systems of this kind aleady developed pesent clea diffeences. Nevetheless, thee ae some common points in almost evey system that it is woth pointing out hee: CAD model. Inspection is based on an exact model of the element. The analysis stage is pefomed off-line. As a esult, a complex data stuctue is obtained. Late, othe modules will use these data. Object pose. Depending on the complexity of the system, the degee of knowledge of object pose vaies geatly. In some cases, object pose detemination becomes a ecognition poblem. Planning. Nomally, thee is a single off-line planning stategy. In the case measuement has not been sufficiently accuate, some authos popose an on-line planning stategy that modifies inspection tasks based on the esults being measued. Calibation. It is necessay to pefom a camea and positioning device calibation stage in ode to be able to pefom measuements. Validation. Based on the esults obtained and the toleances peviously defined, a validation stage detemines whethe the pat is valid o should be ejected.

3 DISAM visual inspection system pesents the following special chaacteistics: Pose detemination stage is vey simple. The accuate pat positioning device the system uses and the pevious knowledge of the stating point has simplified this stage to a basic pose adjustment check pocess. This fact allows us to concentate ou effots in inspection mattes only. Planning is pefomed off-line. The following sections will descibe the foundations on which planning stategy is based on. The system is designed to check featues involved in the opeation of the pat. A set of high level definitions descibes these featues and the basic inspection tasks the system may pefom. Accoding of these points, the opeation of ou system is epesented in figue 1. CAD model Off-line Off-line planne Model infomation classification Inspection definitions file Use On-line Position adjustment Simulation Compaison with the model Rotation and tanslation matixes Calibation Featue inspection stage Toleance analysis and validation Figue 1. System opeation Two diffeent stages may be distinguished in ou inspection model: off-line and on-line stages. 1. Off-line stage. Based on the analysis of the CAD model, an inspection stategy is obtained. This stategy elies on measuements and toleance specifications. 2. Online stage. All the featues to inspect ae analyzed successively. Based on the planning stategy developed in the pevious stage and the system calibation paametes, it is possible to detemine the exact position of the pat to be inspected. The next stage is pefoming inspection and validation. As shown in figues 2 and 3, the system physically consists of the following elements: 1. Image acquisition system. It is made up of a binocula steeo mount (MARCONI) with ten degees of feedom (pan, tilt and vengeance and zoom, focus and iis fo each camea). Nevetheless, the fist two degees of feedom ae fixed duing inspection in ode to avoid inceasing uncetainties. In futue developments, one o two cameas will be added to the system in ode to incease edundancy in measuement and evaluate eliability moe efficiently. 2. Image acquisition and pocessing boad (DATACUBE MAXVIDEO 200). Responsible fo low level image pocessing tasks. 3. Stuctued light system. It consists of a lase plane (MONOCROM) without any degees of feedom, although in futue vesions the plane may have a otation axis. 4. Positioning and oienting system (NEWPORT) with thee degees of feedom.

4 5. CAD wokstation. (SGI O2) fo monitoing and commanding tasks. 6. Pocesso fo intensive mathematical calculations. (DATACUBE MAX860) 7. Wokstation. Fo global contol and high level image pocessing tasks. Figue 2. Simulation of DISAM inspection system Figue 3. View of DISAM inspection system 3. PRECISION Lack of esolution in this kind of systems, as opposed to othes that utilize diffeent techniques, is the fundamental eason fo its poo usage in industial applications. This is not only caused by the implicit difficulty of modeling a system of this complexity but also by the uncetainty intoduced in evey stage of the measuement pocess. One of the factos that have been taken into account duing development is accuacy in measuement. In ode to obtain consistent esults, an uncetainty popagation stategy 9,10 has been caied out. In steeo vision applications, uncetainty may be caused basically by the following factos 11 : Featue extaction algoithms Calibation Steeo matching 3D econstuction Accoding to this, fou diffeent levels of analysis have been consideed Modeling of featue extaction algoithms Ou aim is to obtain a measuement of the quality of featue extaction algoithms. Such measuement is epesented by means of a vaiance and covaiance matix and it is the stating data used in the popagation pocess. Diffeent modeling stategies have been pesented in the liteatue 12, 13, 21. Nevetheless, the pactical applicability of most of these methods is athe

5 difficult. In addition, they seldom etun a quantitative measuement and, when they do, it is oiented to pefom a compaative study between vaious algoithms. In ou system, we have modeled the behavio of those algoithms employed in inspection: edge detection, cone extaction and lase intesection analysis. Ou appoach consists in geneating synthetic images simila to those of the inspection pocess. These images ae coupted by degadations of the kind intoduced duing image acquisition: noise, line-jitte and illumination gadients. Vaiables significant to the behavio of the algoithm have been identified. Accoding to this, fo each one of these vaiables, a test to quantify its impact on the final esult has been designed. Fo example, in the case of cone extaction algoithms, the following factos have been taken into account: oientation, angulaity, image contast, gaussian and andom noise level and closeness between featues. The tue position of the cone is compaed to the position calculated. Accoding to this compaison, a measue of deviation fom ideal is obtained. In the case of edge detection algoithms, a segment is fitted to staight edge points, so the compaison is established between this segment and the tue edge position. Finally, in the case of lase intesection analysis, the points ae fitted to a high level entity such a segment o a cuve. Anothe concept used in ou system is that of logic o genealized senso 11,17 widely used in senso fusion. Oiginally, it was motivated by the idea of defining a geneic senso in a multisenso system. In ou system, the image acquisition and featue extaction algoithm constitute a unique module with a well-defined inteface. The input data is a system state vecto that descibes the values of the system paametes and the values of the significant vaiables of the algoithm as descibed in the pevious paagaph. The output data is the value of the featue extacted and a quantitative measue of its uncetainty. This appoach allows us to easily substitute the image acquisition and featue extaction systems fo diffeent ones and to integate them in the context hee pesented. Nevetheless, a lage developing and modeling pocess must be caied out Calibation. When calibating cameas with motoized lenses, the aim is to obtain a table with intinsic and extinsic paamete values fo a wide ange of vaiation of all the degees of feedom involved. Based on thee-dimensional econstuction of geometic elements of known dimensions, we ae able to obtain an estimation of the amount of eo in the paametes. The main difficulty comes when attempting to identify the potion of the final eo that can be assigned to each paamete. In the case of mechanical device calibation, vaious tests of positioning ae pefomed Steeo matching. Estimation of eliability of measuement and calibation allows one to build analysis windows of size popotional to uncetainty. Theefoe, as fa as we ae capable of impoving accuacy in each individual task, the amount of data to be pocessed will be educed. A geat effot has been done in the aea of outlie detection Thee-dimensional econstuction. In this level, uncetainty popagation is pefomed based on the tiangulation mathematical model and the uncetainty values peviously calculated. The whole pocess follows the ecommendations descibed in CALIBRATION Calibation of a visual system constitutes the most impotant task in thee-dimensional inspection due to its impact on measuement accuacy. The pocess of calibation consists in calculating in a vey pecise way the values of the paametes that detemine the tansfomation between a point P w in thee-dimensional space and the point P c pojected on the CCD plane of the camea. This tansfomation may be epesented in a simplified way as X = M X whee X c =(nx f, nyf, n) T is a vecto with lateal coodinates efeed to the Camea Coodinate System (CCS) and P w efeed to the Wold Coodinate System (WCS). Vecto X c is scaled by the value of n because thee ae infinite points in space that may be pojected onto it. Matix M is called pespective pojection matix and consists of two goups of paametes. That is, P i called intinsic paamete matix, which is elated to the camea itself and P e o extinsic paametes, which define the otation and tanslation of the WCS to the CCS. The composition of both matixes is defined as follows: c w

6 fk M = Pi Pe = 0 0 x 0 fk 0 y Cx C y tx tx t x (1) In this equation, f is the focal distance of the camea, k x and k y elate hoizontal and vetical distances to pixels in the CCD (pixels / mm) and C x and C y locate the cente of the image. On the othe hand, ij ae the elements of the otation matix between WCS and CCS and t j ae the elements of the tanslation vecto between both systems. This set of paametes is usually unknown although, in the case of intinsic paametes, we may have an estimation povided by the manufactue. The way to obtain such paametes is by means of a calibation element as the one shown in figue 4. The thee-dimensional coodinates of the cones of each squae with espect to WCS ae known with accuacy and we can elate them to thei pojection on the image based on the mathematical model of camea and pojection. Both thee-dimensional points and image points allow us to calculate the values of the paametes of the camea by means of means squae adjustment. This model is valid only if a metic o linea camea is being used. Vey often, commecial cameas pesent abeations and geometic and chomatic distotions. In ode to calculate the magnitude of these distotions, a coection pocess may be necessay. Geometic distotions affect the positions of points in image plane in a way that shape of objects and thei pojections do not match. Theefoe, consideing cental coodinates in the CCD plane, it is possible to distinguish between undistoted coodinates and (x u, y u ) distoted coodinates (x d, y d ). The elationship between them is defined as x u =x d +D x (x d,y d ) and y u =y d +D y (x d,y d ). Distotion coection factos D x and D y depend on the position Figue 4. Camea calibation element on the CCD plane on which the point is pojected and the distotion model being consideed. Usually, distotion is modeled as addition of adial and tangencial components and only two adial distotion coefficients: a 1 and a 2 and two tangencial coefficients: p 1 and p 2 appea. Accoding to this, intinsic paametes matix takes the following fom: fk Pi = 0 0 x 0 fk 0 y C K D x y 1 x y x C K D y (2) This stong non-lineaity makes it impossible to solve the poblem using linea least squae methods. Vaious methods fo estimating the value of intinsic and extinsic paametes have been developed. Tsai 22,23 only consides adial distotions. Vanishing point method 24,25 is oiented to cameas with motoized lenses due to the way in which pincipal point is calculated o instead, it uses an estimation of the pincipal point as seed fo solving the algoithm. The two plane method equies the contol points to be distibuted on two planes. It also calculates intemediate paametes that ae function of physical paametes of the cameas. Finally, DLT method 26 has been the one used in this system. It consides the image as distosionless and a fist appoximation fo the values of the intinsic and extinsic paametes is calculated. Based on the eos intoduced by these paametes, distotions ae modeled and its magnitude calculated. The esult is an inaccuate set of paametes although it seves as a good seed fo non-linea optimization using Levenbeg-Maquadt method to minimize esiduals. On the othe hand, in ode to avoid calculating geometic distotion paametes, telecentic lenses may be employed. This way, the pocess of calibation is highly simplified. In ou case, we have used standad lenses due to the high cost of the pevious ones. Neithe a cinematic calibation of the steeo mount has been pefomed because vengeance, azimuth and elevation emain constant duing inspection. Lase plane has been calibated to detemine its position in space with espect to WCS. Calibation consists in calculating the values of the coefficients of the plane of equation A x w +B y w +C z w +D=0. The calibation element is the one shown in figue

7 5. The lase plane intesects with each step and the cente of gavity of each one of these lines is calculated. This set of points constitutes the contol points fo the calibation algoithm. Only thee points ae necessay fo calculating the position of a plane in space but moe numbe of points povide a bette estimation by least squae methods. 5. DATABASE OF ELEMENTS TO INSPECT One of the elements on which inspection is based is the CAD model of the pat. The poblem of managing this infomation comes up. It is necessay to tansfom the pimitives of the gaphic file into high level entities, which ae manageable by the system. Once this is done, the inspection stategy is based on these entities. The featues of these high level entities ae descibed as follows: 1. Geometic paametes: magnitude, efeence system and toleance aea 2. Inspection paametes: accoding to the featue extaction algoithm cetain pivileged diections associated to the entity. This classification lead to develop a table with the definition of the Figue 5. Lase plane calibation element inspection tasks the system is capable of pefoming. The definition of each entity in the list clealy defines the behavio of the diffeent devices in the system and seves as infomation to obtain the inspection planning stategy descibed in the following section. Figue 6 shows examples of some entities in the list. Fo example, if an angulaity measue between two planes is going to be pefomed (figue 6a), accoding to the diections defined by each plane in the CAD model and the database definition, a ange of valid states of the physical devices in the system is obtained. These values epesent a state of the system fom which the inspection of the featue is possible. The analysis of a specific entity often consists in a set of complex opeations o states the system must follow. This set of opeations is encapsulated as a single inspection task associated with that entity. This single inspection task must have a clea inteface. The input data usually consists of pat oientation paametes and state of the optics. Fom this set of paametes the opeations to be pefomed must be peviously simulated and a measue of uncetainty is estimated. The output data consists of the measuement and its eliability by means of a vaiance and covaiance matix. This appoach has the following advantages: It povides a solid famewok fo inspection planning. As explained in the following section, planning is based on inteaction between entities and theefoe, complex inspection tasks may be faced. It clealy defines the applicability of ou inspection system. That is, new enties in the database allow the system to inspect othe featues. It lays the foundations of uncetainty popagation. Unfotunately, the complexity of defining an entity is athe lage. The esults deived fom this system indicate the need of developing automatic calibation methods and simple algoithm modeling techniques. One facto to point out is the indivisibility of pincipal diection of the entity and featue extaction algoithm. Actually, the featue extaction algoithm defines the featues of the entity and the diection of inspection of an entity detemines the pose of the pat to inspect with espect to the featue extaction system (camea and lase).

8 Entity Angle Plane Distance between planes Diagam 6. INSPECTION PLANNING In the planning stage we look fo optimal pose of the pat with espect to the cente of convegence of the cameas and fo the state of the optics fo maximal esolution. The input infomation consists of a list of entities, its toleance zones and efeence systems and the CAD model. This model is teated as a whole, that is, no element in the model is consideed to have any special natue. This is done to identify the influence that each element in the model may have on the inspection of each specific entity. The poblem is posed as the analysis of entities with espect to a efeence system. The output infomation of this stage is the optimal state of the physical elements in the system. It is woth pointing out that the inspection is not simplified as extacting a single measuement but linking such measuement to the opeation of the pat. The extinsic degees of feedom of the system ae vengeance of the steeo mount and the angle between the vecto nomal to the entity and the plane that contain the axes of both cameas. The intinsic degees of feedom ae the state of the optics. In ou system we obtain measuements of visibility and eliability fom the elements database. Simila appoaches based on these measuements o simila have been widely used 16,17. Cylinde Figue 6. Examples of vaious entities. a) Angle, b) plane, c) distance between planes, d) cylinde Visibility citeion (figue 7) equies that the entity to inspect may be visible fom both cameas at that point of view. A valid entity allows the featue extaction algoithm to behave coectly. Usually, this condition is satisfied when a set of opeations is followed. In ode to identify this set of opeations, in the fist place an offline analysis of the CAD model is pefomed and high level entities ae selected. These entities have been associated to a toleance zone and a efeence system fom which the measuement must be pefomed. Eventually thee ae one, two o moe entities elated. We have called this a elationship. The occlusion analysis is based on this elationship and the estictions imposed by the est of the elements in the model. Theefoe, high level entities define valid inspection aeas while the est of elements define invalid inspection aeas. The intesection between both aeas detemines a ange of states fom which each entity is visible. It is impotant to point out that the definition of each elationship elies on the concept pesented at 7 about efeence systems and simulated elements. Reliability citeion seaches, among visible states of the system, a sequence of viewpoints and pat oientation states such that inspection is optimal. In the case of using stuctued light the citeion is based on the optimal eflection of the lase beam on the suface of the pat 14. In the case of using othe featue extaction technique, the visible aea of the pat is maximized.

9 Entity 1 Entity 2 Entity n + Relationship Thee ae occlusion poblems Visibility analysis of the CAD model + No occlusion poblems State of inspection Figue 7. Visibility citeion In geneal, if a single entity is being inspected, the definitions of entities in the database specify pefectly the steps to follow. Nevetheless, if we ae dealing with a elationship, thee diffeent inspection stategies have been poposed: All the entities that make up the elationship ae visible fom a single point of view without tanslating o otating the pat and the esolution is sufficient to meet toleances (figue 8a). In this example, fom a single point of view the angle between both planes may be measued by calculating the nomal vecto to each plane. All the entities that make up the elationship ae visible fom a single point of view but the esolution is not sufficient to meet toleances (figue 8b). In this case, although thee is a point of view fom which all the dill holes ae visible it is necessay to analyze each one of them sepaately and change the point of view. The uncetainty intoduced by this change in the point of view must be taken into account All the entities that make up the elationship ae not visible fom a single position. Theefoe, the pat has to be tanslated and otated (figue 8c). Just like in the pevious case, the uncetainty caused by the change of position o point of view must be consideed. Accoding to these two citeia and the type of elationship being consideed, a set of opeations (sometimes called inspection lists) is obtained. If any facto about inspection has to be optimized (inspection time...), diffeent appoaches may be poposed. Ou choice is establishing a set of weights accoding to the impotance of the entity. Fo example, accuate location of a efeence plane may have geat impact in the final measuement. Theefoe, a lage weight may be associated to it. Nevetheless, these factos have not been studied in depth and constitute a futue eseach aea. Regading the compaison between model and eal data, thee ae some examples in the liteatue in which the alignment between both efeence systems is not optimal 8. In othe examples, planning stategies oiginally developed fo ecognition o pose estimation ae being used 6. In all these cases, the natue of elements being inspected is not taken into account. In ou system, because of the stategy of analysis of high level entities and thei efeence systems, we can establish consistent measuements and compaisons.

10 Figue 8. Inspection stategies based on elationships 7. CONCLUSIONS In the fist place, a new appoach based on high level geometic entities constitutes a consistent famewok fo inspecting thee dimensional machine pats. Planning of inspection is developed in a natual way and the aim of analyzing specific entities accoding to opeation of the pat may be fulfilled. On the othe hand, uncetainty popagation impoves notably the esults obtained. In this sense, it is clea the high dependence that exists between final esults and calibation of physical devices. It is woth pointing out the need of impoving calibation techniques both in obustness and simplicity of application. It is also clea the complexity of estimating quantitatively the eos intoduced in evey stage of inspection especially duing algoithm modeling. Assignation of eos to each paamete of the camea model is also a vey difficult task. The system developed allows one to think this kind of applications may be an altenative to othe non-visual inspection systems in which flexibility is needed. Uncetainty popagation techniques togethe with an impovement of esolution of physical devices lead towads a bette pecision in measuement. Nevetheless, it is clea that the esolution obtained still constitutes a limit to its applicability. As futue eseach woks we plan to incopoate one o two cameas to the system in ode to incease edundancy in measuement and impove eliability. On the othe hand, the database of high level entities and elationships must be lage to allow citeia to develop inspection lists become moe complex and ealistic. Finally, it is necessay to study calibation in depth due to the fact that, nowadays, they mean the most impotant limit to this kind of systems. REFERENCES 1. Mewman, Jain. A suvey of automated visual inspection, CVIU (61), 2. Mach K. B. Atkinson. Close ange photogammety and machine vision. Whittles Publishing, Mikell P. Goove, E. W. Zimmes. J. Compute aided design and manufactuing. Pentice Hall, W. Winchell. Inspection and measuing in manufactuing. Society Manufactuing Enginees, Taek M. Sobh, Jonathan Owen, Chis Jaynes, Mohamed Dekhil, Thomas C. Hendeson. Intemediate esults in active inspection and evese engineeing, Intenal epot. Depatment of Compute Science. Univesity of Utah. 6. A. D. Mashall, R. R. Matin. Compute vision, models and inspection. Wold Seies in Robotics and Automated Systems, vol B. R. Modayu, L. G. Shapio, R. M. Haalick. Visual inspection of machine pats, In Advances in Image Pocessing and Machine Vision, J. Sanz, ed. Spinge- Velag, G. H. Tabox, S. N. Gottschlich. IVIS: an integated visual inspection system, CVIU (61), 3, R. M. Haalick. Popagating covaiance in compute vision, Poc. of 12 th IAPR, O. Faugueas. Thee-dimensional compute vision. A geometic viewpoint. MIT pess, Z. Zhang, O. Faugueas. 3D dynamic scene analysis. Spinge Seies in Infomation Sciences. Spinge-Velag, Neil Thacke. Tina algoithm's guide (Afte geometic vision). Univesity of Sheffield. May, 1997

11 13. Patic Coutney, Neil Thacke, Adian Clak. Algoithmic modeling fo pefomance evaluation, Machine Vision and Applications (9), James Clack, E. Tucco, L. B. Wolff. Using light polaization in lase scanning, IVC 15, W. Heckel. Use of CCD cameas fo digital image pocessing: synchonization and souces of eo, Optical 3-D measuements techniques II. Wichmann, K. Ikeuchi, T. Kanade. Modeling sensos: Towad automatic geneation of object ecognition pogam, CVGIP (48), E. Tucco, M. Umasuthan, A. M. Wallance, V. Robeto. Model based planning of optical senso placement fo inspection, IEEE Tansactions on Robotics and Automation Vol. 13, nº 2, Apil, C. S. Fase. Automation in digital close-ange photogammety, Fist Tans. Tasman Suveyos Confeence, Apil. Newcastle, Repot on the BIPM inquiy on eo statements. Rapot BIPM-80/3, Bu. int. poids et measues. English vesion. (Sèves, Fance) 20. J. H. Vandenbande, A. G. Requicha. Spatial easoning fo the automatic ecognition of machinable featues in solid models, IEEE PAMI, vol 15, nº 12, Decembe, H. I. Chistensen, W. Föstne. Pefomance chaacteistics of vision algoithms, Machine Vision and Applications, vol. 9, 516, Konstantinos Taabanis, Roge Y. Tsai and Douglas S. Goodman. Modeling of compute contolled zoom lens, IBM Reseach Division Konstantinos Taabanis, Roge Y. Tsai and Douglas S. Goodman. Calibation of a compute contolled obotic vision senso with a zoom lens, IBM T.J. Watson Reseach Cente. Yoktown Heights. New Yok M.J. Magee and J.K Aggawal. Detemining vanishing points fom pespective images, Laboatoy fo Image Signal Analisys, Univesity of Texas G.F. Mac Lean and D. Kottui. Vanishing point detection by line clusteing, Depatment of Mechanical Engineeing. Univesity of Victoia (Canada), Janne Heikkilä, Olli Silvé. A fou-step calibation pocedue with implicit image coection., Univesity of Oulu (Finland), 1997

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