Abstract:
A method of recalibrating to compensate for thermal drift between a micro-imaging system and a sample integrated circuit (IC) under investigation determines a planar drift using a cross-correlation between a reference calibration image and a recalibration image, and further determines a focus drift from a difference between a reference focus setting and a recalibration focus setting. The recalibration is performed on detection of a recalibration trigger event, such as expiry of a recalibration time interval. The recalibration time interval can be adaptively adjusted based on a magnitude of the thermal drift. Tile images captured since a last recalibration are recaptured if the thermal drift is too great for reliable image compensation. The system ensures seamless assembly of tile images into image photo-mosaics and increases image photo mosaic throughput.

Description:
TECHNICAL FIELD 
     The invention relates to the field of micro imaging and, in particular, to methods of recalibration to compensate for thermal drift between a micro-imaging system and a sample under investigation. 
     BACKGROUND OF THE INVENTION 
     Semiconductor integrated circuits (ICs) are reverse-engineered for the purposes of validation and product quality assurance. Typically a large group of high magnification tile images representative of a sample IC are acquired using a high magnification micro-imaging system in between deconstructive steps. Subsequent processing of the tile images includes their assembly into one or more photo-mosaics. Each photo-mosaic is representative of the IC sample, or portion thereof, at a particular deconstructive step. 
     Representative dimensions that have to be resolved by the micro-imaging system are related to the width of traces, which are connections between components on the ICs. Trace width reduction is a goal sought in the semiconductor manufacturing industry to provide increased integration, increased switching speed, reduction in drive voltages, etc. Today typical trace widths are in the micron and submicron range. 
     The time required for micro imaging an IC sample at each deconstructive step is typically on the order of hours or days. It is well known in the art of material sciences that all known materials are subject to temperature induced deformation. The degree of deformation is dependent on a particular material&#39;s coefficient of thermal expansion. A high magnification optical microscope is commonly used in micro imaging. The microscope typically has an arm supporting high magnification optic elements above the sample IC. It has been observed that the components of the micro-imaging system are subject to temperature induced deformation. It has also been observed that the temperature-induced deformation is time dependent, typically having a linear variation. This phenomenon is commonly referred to as “thermal drift”. Thermal drift between the optics and the sample IC during micro imaging can cause misalignment between images acquired at different times. It will be understood by those skilled in the art that an imaging system other than optical, such as a beam instrument as used in a Scanning Electron Microscope (SEM) or Focus Ion Beam (FIB), could also be used. 
     Considering the size of the arm of the optical microscope and coefficient of thermal expansion of the materials used in manufacturing the arm (such as aluminum), thermal drift can sometimes cause a misalignment in excess of 20 microns cumulative between images. Therefore, thermal drift can be a significant impediment to acquiring high magnification images and assembling the images into photo-mosaics representative of a surface of interest of the IC sample. 
     Misalignments between the optical system and the IC sample during micro-imaging result in either an excess of overlap between the acquired images, or the formation of inter-image gaps. Having excess overlap leads to waste processing time. Having incomplete mosaics due to inter-image gaps results in an inability to validate the IC design. One option for reducing thermal drift is to wait for the temperature of the sample IC and imaging apparatus to stabilize, assuming stable temperature conditions. However, suitable conditions are very rare. Another option is to enforce dynamic temperature control during the micro-imaging process. This is an expensive option that is difficult to achieve in practice, at least partly because the image acquisition process itself generates heat because the sample IC is positioned for each image acquisition by an electromechanical drive mechanism that generates heat when operated. Other factors related to temperature control are heat capacity and heat conductivity coefficients of materials, which impose limits on how quickly, and at what cost dynamic temperature control can be effected. 
     There therefore exists a need for methods and apparatus for dynamically recalibrating a micro-imaging system to compensate for thermal drift. 
     SUMMARY OF THE INVENTION 
     It is an object of the invention to provide a method of determining thermal drift between a micro-imaging system and a sample to compensate for temperature-induced deformation. 
     It is another object of the invention to ensure compensation for misalignment between a micro-imaging system and an imaged sample based on measured thermal drifts determined during a photo-mosaic acquisition period. 
     It is a further object of the invention to provide a method of determining thermal drift between the micro-imaging system and the sample at predetermined time intervals during a photo-mosaic acquisition period. 
     It is a further object of the invention to provide a method of determining thermal drift between the micro-imaging system and the sample based on an adaptive recalibration time interval responsive to a rate of thermal drift. 
     In accordance to one aspect of the invention a method is provided for determining a measure of thermal drift between the micro-imaging system and a sample. The method includes an initial calibration step performed prior to an acquisition of a series of high magnification images of a surface of interest of the sample. The initial calibration includes positioning a pre-selected calibration location on the sample in a field-of-view of the micro-imaging system, determining a reference calibration focus setting by focusing the micro-imaging system on the sample at the pre-selected calibration location and capturing a reference calibration image. The recalibration is triggered during the acquisition of the images to determine the thermal drift. The thermal drift determination includes repositioning the pre-selected calibration location in the field-of-view of the micro-imaging system, determining a recalibration focus setting, capturing a recalibration image, determining a planar shift from a correlation between the reference calibration image and the recalibration image. The determined planar shift and a difference between the reference calibration focus setting and the recalibration focus setting represent the measure of thermal drift between the micro-imaging system and the sample. 
     A method is provided for acquiring high magnification tile images of an integrated circuit sample using an optical system subject to thermal drifts. A field of view of a high magnification power optical system is positioned over a surface of the sample at a predetermined location. A tile image of the surface is captured and stored. On detecting a trigger event, a thermal drift between the optical system and the sample is determined with respect to a predetermined calibration location on the surface of the sample. The acquisition of tile images is continued in accordance with predefined rules respecting a degree of thermal drift. The rules include aborting tile image acquisition in the event of excessive thermal drift, recapturing all tile images since a last recalibration in the case of a large thermal drift, and otherwise continuing tile image acquisition. 
     In accordance with another aspect of the invention the trigger event includes the expiration of a recalibration time interval and the recalibration time interval is adaptively varied based on rules respecting the degree of the thermal drift. As such the recalibration time interval is increased when thermal drift is slight and decreased when thermal drift is significant. Other rules ensure that recalibrations are performed during the tile image acquisition period, and that recalibrations occupy only a certain amount of processing time. 
     The invention also provides a micro-imaging system for acquiring high magnification tile images of a sample while the system is subject to thermal drift, the tile images being used to construct a seamless photo-mosaic of a surface of interest of the sample. The micro-imaging system comprises means for positioning the surface of interest in a field of view of a micro-imaging system at a location on the sample; means for storing a position of the location; means for focusing the field of view of the micro-imaging system on the surface of interest; means for capturing an image of the surface of interest; means for storing the captured image; means for detecting a trigger event for determining a thermal drift between the micro-imaging-system and the sample; means for determining a thermal drift between the micro-imaging system and the sample in response to the triggering event; and means for controlling the micro-imaging system in accordance with predefined rules respecting the capture of the tile images, the rules being related to an extent of the thermal drift since a last trigger event. 
     The means for positioning the surface of interest in a field of view of a micro-imaging system at a location on the sample comprises a stage of the micro-imaging system. Algorithms that are executed by a computer workstation control the stage. 
     The means for determining the thermal drift comprises an algorithm for capturing and storing an in-focus calibration image of a predetermined calibration location on the surface of interest and a focus setting used to capture the calibration image. An algorithm that controls the micro-imaging system returns the system to the calibration location on detection of the trigger event and captures and stores an in-focus recalibration image of the predetermined calibration location on the surface of interest and a focus setting used to capture the in-focus recalibration image. 
     The means for determining the thermal drift further comprises an algorithm for cross-correlating the calibration image and the recalibration image to determine a planar shift of the micro-imaging system with respect to the surface of interest, and for computing a difference between the calibration and the recalibration focus settings. The algorithm for cross-correlating the calibration image uses a Fourier transform of the calibration image and a Fourier transform of the recalibration image to determine a planar shift along the surface of interest of the recalibration image with respect to the calibration image. 
     The means for interpreting the predefined rules comprises an algorithm for comparing the extent of the thermal drift to at least one threshold to determine a next action dependent on the extent of the thermal drift with respect to the at least one threshold. 
     A re-settable clock counter is preferably used for tracking the recalibration interval. The algorithm preferably doubles the recalibration interval if the extent of the thermal drift is less than a recalibration-doubling threshold. The algorithm preferably halves the recalibration interval if the extent of the thermal drift exceeds a recalibration-halving threshold. The algorithm preferably does not change the recalibration interval if the extent of the thermal drift is greater than the doubling threshold but less than the halving threshold. The algorithm preferably controls the micro-imaging system to backtrack to a location on the surface of interest to recapture the images taken since a last recalibration if the extent of the thermal drift exceeds a recapture threshold, and the algorithm preferably abandons image capture if the extent of the thermal drift exceeds an abort threshold. In addition, if the recalibration interval is doubled, the algorithm preferably compares the doubled recalibration interval with a predetermined maximum recalibration interval and sets the recalibration interval to the predetermined maximum recalibration interval if the doubled recalibration interval exceeds the predetermined maximum recalibration interval. If the recalibration interval is halved, the algorithm preferably compares the halved recalibration interval with a predetermined minimum recalibration interval and sets the recalibration interval to the predetermined minimum recalibration interval, if the halved recalibration interval is less than the predetermined maximum recalibration interval. 
     The focusing algorithm preferably performs a coarse focus search by capturing a series of images at a plurality of coarse focus settings and selecting a best coarse focus setting based on a derived focus measure for each captured image until a peak coarse focus measure is located. The focusing algorithm then performs a fine focus search centered around the peak coarse focus setting by capturing a series of images at fine focus settings and selecting a best fine focus setting based on a derived focus measure for each captured image in the fine focus search. 
     The advantages include an automated image capture system that enables seamless assembly of tile images into photo-mosaics, and an improved throughput of tile image mosaics. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     Further features and advantages of the present invention will become apparent from the following detailed description, taken in combination with the appended drawings, in which: 
     FIG. 1 is a work flow diagram showing an overview of an exemplary process by which photo-mosaics representative of steps in a deconstruction of a semiconductor integrated circuit (IC) are acquired; 
     FIG. 2 is a process diagram showing an exemplary progression of steps in manufacturing an IC; 
     FIG. 3 is a process diagram showing an exemplary progression of steps in deconstructing of an IC for reverse engineering; 
     FIG. 4 shows an example of a micro-imaging system comprising a computer controlled optical stage, an imaging system such as a high magnification power microscope and a digital imaging system such as a Charge Coupled Device (CCD) camera; 
     FIG. 5 is a flow diagram showing a process in accordance with the invention by which a micro-imaging system acquires high magnification tile images of an IC sample that is subject to temperature induced deformation; 
     FIG. 6 is an action diagram showing a response of an adaptive recalibration algorithm performed by the micro-imaging system in accordance with the invention to optimize the duration of a recalibration time interval; 
     FIG. 7 is a flow diagram showing the process in accordance with the invention by which an initial calibration of the micro-imaging system is achieved; and 
     FIG. 8 is a flow diagram showing the process in accordance with the invention by which thermal drift between the micro-imaging system and the sample IC is determined. 
     It will be noted that throughout the appended drawings, like features are identified by like reference numerals. 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
     FIG. 1 is a work-flow diagram showing an overview of an exemplary prior art process by which photo-mosaics representative of steps in the deconstruction of a semi-conductor integrated circuit (IC) are acquired. ICs  10  are fabricated on a wafer  12 . The wafer comprises a mono-crystalline silicon substrate, which is naturally an insulator. Doping the silicon with other chemical elements can change the properties of the silicon, including making the silicon a semi-conductor or a conductor. Such substrate processing is performed as part of a manufacturing process  14  of integrated circuits  16 . In packaging an IC  16 , a die  20  is cut in a step  18  from the wafer  12  and is encapsulated in step  22  to form a chip. 
     The manufacture of integrated circuits typically involves a verification process  24  by which wafers  12  or cut dies  20  are inspected using a micro-imaging system  26  to extract design and layout information for design validation of ICs  10 . 
     For the purposes of product quality assurance, or to reconstruct electric circuits for competitive analysis, for example, a process of reverse-engineering  28  is performed on the integrated circuit  16 . A first step in the reverse-engineering process  28  is decapsulation  30  of the IC  16  to remove the die  20 . Die  20  is inspected using a micro-imaging system  26  to extract design and layout information. The micro-imaging system  26  may include high magnification optical microscopes, scanning electron microscopes, field emission electron microscopes, or the like. Design and layout extraction from a die  20  involves, as shall be described below with respect to FIG. 3, a process of deconstruction  32  by which layers formed during the manufacturing process  14  are removed. 
     High magnification tile images  34  of the sample die  20  are acquired between each deconstructive step  32  under the control of a computer workstation  36 . The computer workstation  36  controls the micro-imaging system  26  using control signals  38 . The computer workstation  36  receives tile image data  40  from the micro-imaging system  26  and saves the tile image data  40  to memory, typically physical storage  42 , such as a hard disk. 
     The stored tile images  34  are assembled into photo-mosaics  44 , each photo-mosaic  44  representing a surface, or portion thereof, of the die  20  at a deconstructive step  32 . During acquisition of the tile images of the die  20 , a sample coordinate space  46  is defined. The sample coordinate space  46  is used to align the photo-mosaics  44 . 
     FIG. 2 is a process diagram showing an exemplary prior art progression of steps followed during the manufacture of an IC. The diagram shows a progression of cross-sections through a silicon substrate, representing exemplary steps in manufacturing a component such as a junction. In step  52  of the progression, the silicon substrate is doped using diffusion and/or ion implantation techniques to change its characteristics and, in particular, to form P-wells, well known in the art. In step  54 , another implantation is performed to form n-type sources and drains. A gate oxide layer is deposited between the sources and drains, and a field oxide is deposited in other areas of the chip in step  56 . A polysilicon gate layer is deposited in step  58 , and in steps  60  and  62  the deposition of oxide layers is effected. Metal layers for providing connectivity between the gates, sources and drains are deposited in step  64 . Step  66  illustrates the deposition of a passivation layer, typically used to protect the IC from physical damage and/or contamination with dust particles before it is encapsulated in step  22  (FIG.  1 ). 
     FIG. 3 is a process diagram showing an exemplary prior art progression of deconstructive steps used to reverse-engineer a sample IC. Step  70  illustrates a cross-section through a silicon substrate of a die  20  after decapsulation in step  30  (FIG.  1 ). Steps  72 ,  74 ,  76 ,  78 ,  80  and  82  illustrates a progressive removal of the deposited material layers, such as the passivation layer, metalization layers, polysilicon layers, base contact layers, the field oxide layer, etc. This results in an exposed silicon substrate (step  82 ) including the well structures manufactured during steps  52  and  54  (FIG.  2 ). In order to reveal the well structure, the back surface of the die  20  may also be deconstructed. Steps  84  and  86  show the progressive deconstruction of the back surface of the die  20  to expose the P- and N-wells. In extracting design and layout information both surfaces of the die  20  may be micro-imaged, and therefore both represent surfaces of interest. 
     FIG. 4 shows a prior art example of a micro-imaging system used to acquire tile images of a sample IC. The micro-imaging system  26  typically includes an optical stage schematically illustrated in the diagram at  100 . The optical stage  100  provides positioning of the die  20  with respect to the high magnification microscope  110 . The optical stage  100  has a vertical axis of displacement  102  and two horizontal axes of displacement  104  and  106 . Collectively the axes of displacement  104  and  106  provide motion of the die  20  in a field of view of the microscope  110 . Axis of displacement  102  provides positioning of the die  20  in a direction perpendicular to the field of view of the microscope  110  and therefore enables focusing of high magnification optics of the microscope  110  onto a surface of the die  20 . The microscope  110  is displaced away from the die  20  by an arm  120 . It is known that the components of the microscope  110 , including the arm  120  are subject to temperature induced deformation (expansion/contraction) which induces misalignment (thermal drift) between the microscope  110  and the die  20 . 
     Acquisition of tile images  34  is facilitated by a digital imaging system such as a Charge Coupled Device (CCD) camera  130 . The optical stage  100  and CCD camera  130  receive control signals  38  from a computer workstation  36  to position the die  20  and move it into focus under the microscope  110 . Other control signals  38  effect the capture of tile images  34  (FIG. 1) which are transferred as digital data  40  to the computer workstation  36 . 
     FIG. 5 is a flow diagram illustrating principal steps in a process in accordance with the invention by which an optical system is adapted to acquire high magnification tile images of an IC sample while subject to thermal drift. 
     The tile image acquisition process begins in step  202 . A recalibration time interval is set to a predetermined default value in step  204 . The default time interval typically has a duration required to acquire about 30 tile images. An initial calibration of the optical system  26 , and in particular of the position of the microscope  110  with respect to the die  20 , is performed in step  206 . The initial calibration is described in more detail with reference to FIG.  7 . 
     A tile image acquisition cycle is initiated in step  208  in which a number of tile images captured since a last recalibration is set to zero. A time counter that stores a time since the last recalibration is set to zero in step  210 . The optical stage  100  is moved in step  212  to a position in the sample coordinate space where the next tile image  34  (FIG. 1) is to be captured. The tile image  34  is captured in step  214  and the captured tile image data is stored in memory in step  216 . The number of tile images captured is then incremented by 1 in step  218 . In step  220 , the tile image acquisition process checks to determine whether the time elapsed since the time counter was set to zero in step  210  is greater than a current recalibration interval. If the time elapsed is less than the current recalibration interval, the tile image acquisition process checks (step  222 ) to determine whether the tile image  34  just captured in step  214  is the last tile image of a photo-mosaic. If not, the process continues at step  212  by moving the optical stage  100  (FIG. 4) to a position to capture the next tile image  34 . 
     If it is determined in step  220  that the time elapsed is greater than the current recalibration interval, or if it is determined in step  222  that the tile image captured in step  214  is the last tile image of the photo-mosaic  34 , a determination of thermal drift is performed in step  224 . The determination of thermal drift will be described below with reference to FIG.  8 . 
     Having determined the thermal drift in step  224 , a decision is made in step  226  as to whether the thermal drift is greater than a tile image acquisition abort threshold. If the thermal drift is greater than the tile image acquisition abort threshold, the acquisition of tile images  34  is aborted in step  228 . If the thermal drift is determined to be lower than the tile image acquisition abort threshold in step  226 , a further decision is made in step  230  as to whether the thermal drift is greater than a tile image recapture threshold. If the thermal drift exceeds the tile image recapture threshold, in step  234  the tile image acquisition process is backtracked to a tile image position stored in step  260  and the image acquisition process resumes at step  208  to recapture all of tile images  34  captured from the position stored in step  260 . 
     If the last captured tile image  34  (FIG. 1) is determined in step  238  to be the last tile image in the photo-mosaic, tile image acquisition is ended in step  228 . 
     In accordance with the invention, the recalibration time schedule may be static or adaptive. A soft toggle is preferably used to activate or deactivate adaptive recalibration. In step  240  it is determined whether adaptive recalibration is activated or deactivated. If adaptive recalibration is deactivated, the tile image acquisition process continues by storing the thermal drift information in step  260  for use in assembling the photo-mosaic as will be explained below in more detail. The position of the last tile image (step  214 ) that was acquired prior to the determination (in step  224 ) of the thermal drift is also stored in step  208  in case the system must be backtracked to the stored coordinates in step  234 . 
     If it is determined in step  240  that adaptive recalibration is activated, adaptive adjustment of the recalibration time interval is initiated in step  242 . A decision is made in step  242  whether the thermal drift determined in step  224  is greater than a threshold for halving the recalibration time interval. If the thermal drift is greater than the threshold for halving the recalibration time interval, the recalibration time interval is reduced to half of its current duration in step  244 . A check is then made in step  246  to ensure that the recalibration time interval is not lower than a minimum recalibration time interval. The minimum recalibration time interval is set high enough to ensure that the micro-imaging system  26  does not spend an excessive amount of time recalibrating. On the other hand, the minimum recalibration time interval is set low enough to ensure frequent recalibration during periods of high thermal drift. If in step  248  the halved recalibration time interval is found to be lower than the minimum recalibration time interval, the recalibration time interval is set to the minimum recalibration time interval. The image acquisition process continues with storing the thermal drift in memory for later use in resembling the photo-mosaic (step  260 ), as will be explained below in more detail, and storing the coordinates of the last tile image captured in step  214 . 
     If the temperature drift is determined to be lower than the threshold for halving the recalibration time interval in step  242 , the adaptive recalibration algorithm checks in step  250  whether the thermal drift determined in step  224  is lower than a threshold for doubling the recalibration time interval. If the thermal drift is lower than the threshold for doubling the recalibration time interval, the current duration of the recalibration time interval is doubled in step  252 . A comparison is made in step  254  to determine whether the recalibration time interval is greater than a maximum recalibration time interval. The maximum recalibration time interval is set to ensure that recalibrations are performed during the acquisition of tile images, even if thermal drift is minimal. If the doubled recalibration time interval is greater than the maximum recalibration time interval, the recalibration time interval is set to the maximum recalibration time interval in step  256 . 
     If it is determined that the thermal drift is not lower than the threshold for doubling the recalibration time interval in step  250 , and if the thermal drift is not higher than the threshold for halving the recalibration time interval in step  242 , then the process resumes at step  260 . 
     In step  260 , the thermal drift and new focus setting are stored in memory, along with the recalibration time, so that the thermal drift (x, y coordinate shift) can be used to assemble the captured tile images  34  (FIG. 1) into a seamless photo-mosaic  44 . In assembling the photo-mosaic using the thermal drift information stored in step  260 , it is assumed that the thermal drift varied linearly during acquisition of tile images  34  captured between recalibrations. The coordinates of the last tile image captured in step  214  is also recorded in step  240 , as explained above. The tile image acquisition process then resumes at step  208 . 
     FIG. 6 is an action diagram illustrating the predefined rules governing the actions of the adaptive recalibration process. It can be seen in the action diagram that as the magnitude of the thermal drift increases the value of the tile images captured decreases. Likewise, as the magnitude of the thermal drift increases, the more frequently recalibration is required to ensure that useable images are captured. 
     If the magnitude of the thermal drift is less than the doubling threshold  280 , the images captured are valid and the recalibration time interval is doubled, but is not permitted to exceed a predefined maximum, as explained above. If the magnitude of thermal drift is greater than the doubling threshold  280  but less than the halving threshold  282 , the recalibration time interval is left unchanged. If the magnitude of the thermal drift exceeds the halving threshold  282  but is less than the recapture threshold  282 , the recalibration time interval is halved, but is not permitted to become shorter than a predetermined minimum, as explained above. If the magnitude of the thermal drift is greater than the recapture threshold but less than the abort threshold, the tile images  34  (FIG. 1) captured since the last recalibration are recaptured. If the magnitude of the thermal drift exceeds the abort threshold  286 , all tile images  34  captured for the mosaic  44  are discarded, a new recalibration point is acquired and the process is restarted from an initial calibration process, which is explained below with reference to FIG.  7 . 
     The preferred embodiment of the invention described above uses elapsed time as a recalibration trigger. The initial recalibration time interval corresponds to a time interval required to capture about 30 tile images. Persons skilled in the art will understand that a recalibration trigger can be based on the number of tile images acquired since a last recalibration, rather than an elapsed time interval. Also, the use of adaptive recalibration can optimize the number of tile images captured between recalibrations. 
     FIG. 7 is a flow diagram showing a process by which an initial calibration of the optical system is achieved. An initial calibration is performed each time a photo-mosaic image capture is begun. The initial calibration of the optical system begins in step  302 . The optical stage  100  (FIG. 4) is moved to a pre-selected calibration location in step  304 . The pre-selected location is a point on the surface of interest with good structural definition. The pre-selected location is chosen such that no repetitive features in the layout of the location are present in the field of view of the micro-imaging system. Repetitive features self-correlate when the thermal drift causes displacement of the image capture system with respect to the sample die  20  (FIG. 1) a distance that is approximate any multiple of a spacing between the repetitive features. An auto-focus algorithm, described below, is run in step  306  in order to extract a reference focus setting at the pre-selected calibration location in step  308 . The reference focus setting is stored in memory, preferably permanent storage, in step  310 . Grey scale imaging is activated in step  312 . A gray scale image is required for thermal drift determination, which is explained below in more detail. A reference calibration image of the pre-selected calibration location is captured in step  314 . The captured image is stored in memory, preferably permanent storage, in step  316 , and the imaging mode is reset in step  318 . The initial calibration process ends in step  320 . 
     FIG. 8 is a flow diagram showing a process in accordance with the invention by which thermal drift of the image capture system with respect to the sample die  20  is determined. The determination of the thermal drift starts at step  402  by moving the optical stage  100  (FIG. 4) to the pre-selected calibration location in step  404 . The pre-selected calibration location is the same one used in step  306  (FIG.  7 ). An auto-focus algorithm is run in step  406  to obtain a recalibration focus setting in step  408 . Grey scale imaging is activated in step  410 . A recalibration image is captured in step  412 , and the imaging mode is reset in step  414 . In step  416 , a process of cross-correlation is performed between the recalibration image captured in step  412  and the reference calibration image captured in step  314  (FIG.  7 ). The cross-correlation is preferably performed using a Fourier transform, as will be explained below in more detail. The cross-correlation process determines the thermal drift in step  418 . The thermal drift determination process ends in step  420 . 
     In capturing images at high magnification, a depth of field of the captured image is very thin. The thin depth of field enables accurate focusing and therefore focus drift determination. Focus drift determination is based on a difference between the reference focus setting and the recalibration focus setting. 
     In accordance with a preferred embodiment of the invention, a focus setting determination is achieved by selecting the focus setting used in capturing a best focus image from a series of images captured at monotonically varying focus settings. The auto-focus algorithm positions the sample die  20  (FIG. 1) by moving the optical stage  100  along the vertical axis  102  (FIG. 3) at focus settings below and above a current focus setting. A coarse focus search is first performed by moving the optical stage  100  in coarse increments. The optical stage  100  is then moved in fine increments for a fine focus search. Images in the series are captured at each focus increment. A focus measure is derived from each image in the series. Preferably, the focus measure is an image sharpness measure, but other focus measures can also be used. Various algorithms for calculating the sharpness of an image are known to persons skilled in the art. The auto-focus algorithm uses the focus measure to select the best focused of the images in the series. The variation in the focus measure may be monotonically varying or peaked. 
     If the variation in the focus measure is monotonic then the best focus setting corresponds to the focus setting of the image having the highest focus measure. However, the auto-focus algorithm is preferably rerun in a search from the highest focus measure to determine if a peak focus measure can be located. If the variation in the focus measure is peaked, then the focus image capture continues, preferably in fine increments centered around the highest focus measure in the peak to find an image having the highest focus measure located during the focus search. In accordance with the preferred embodiment of the invention, focus searching is performed using coarse and fine increments. However, other autofocusing algorithms may be used. 
     The cross-correlation step  416  (FIG. 8) described above can be performed by correlating the recalibration image to the reference calibration image. In general terms thermal drift determination involves determining planar shifts between the recalibration image and the reference calibration image. According to the preferred embodiment of the invention, the recalibration image and the reference calibration image are transformed using a Fourier transform, well known in the art. The Fourier transform of the reference calibration image and the Fourier transform of the recalibration image are cross-correlated. The cross-correlation of Fourier transforms of images is known in the art of image processing. Other methods for determining a planar shift between two images of the same structure are also known in the art, and the invention is not limited to using Fourier transforms for cross-correlation of the images. 
     The embodiments of the invention described above are intended to be exemplary only. The scope of the invention is therefore intended to be limited solely by the scope of the appended claims.