reference is now made to fig1 , which is a generalized diagram showing fluorescent imaging apparatus for taking images of fluorescing samples . an apparatus 10 comprises a fluorescent microscope 12 , connected to a camera 14 and to a motorized focus mechanism 20 , all of which are connected to a computer 16 . the computer is preferably connected to receive data from and to control both the camera and the motorized focus 20 . the microscope 12 preferably comprises an illumination source 18 for illuminating a fluorescent sample . emitted , reflected and fluorescent light is received back at the microscope 12 . as is common in microscopy , the illumination source 18 is preferably situated behind the objective lens of microscope 12 , so as to illuminate the sample via the objective lens . such a form of illumination has two effects , firstly that it concentrates illumination in the focal plane and secondly that it reduces noise in the image since the microscope picks up only emitted light and not transmitted light . preferably , the apparatus is provided with a light intensity measurement unit 20 arranged to measure light intensity levels of the sample as gathered by the objective lens . preferably the light intensity is measured on a per pixel basis . preferably , the light intensity measurement unit is associated with control of the distance between the objective lens and the sample . generally the sample , or more precisely the sample mounting stage is moved , in order to carry out focusing . in principle it is also possible to move the objective lens , but such is not usually done . the distance is controlled in response to light intensity measurements , preferably using motorized focus mechanism 20 . as mentioned above , the use of the objective lens as a route for the illumination light ensures that the image is most highly illuminated when it is in the focal plane . thus , measured light intensity reaches a maximum when the sample is in the focal plane of the objective lens . hence it is possible to control changes of the focus distance to maximize the intensity signal , thereby focusing on the sample . the above principle works as long as the sample is not large relative to the field of view . if the sample is large than it has the effect of integrating the light signal to give an overall light intensity which is high even when the sample is not focused . methods for removing large objects from consideration will be discussed below . in one preferred embodiment of the present invention a focusing procedure is carried out in which the camera is set to a fast exposure rate and then a series of images are taken . light intensity is measured at each image to determine an image which has a maximum light intensity . the motorized focus is moved to a position corresponding to the image having the maximum light intensity and the microscope is now focused . referring now to fig2 , the focusing procedure of the above embodiment is discussed in more detail as follows : first of all the camera is set to its focus parameters , namely to a setting of fast exposure and high gain , and a set of images is taken at different focusing positions . the following procedure is then carried out with the first image to obtain threshold levels and a mask to remove large objects and keep only small objects . the average intensity i av and standard deviation , σ ; are computed for the first image . the image is thresholded using the image threshold t h = i av + k * σ , where k is a constant . a typical value for k would be 3 . removal of large objects from the image is carried out using a process known as blob analysis . in blob analysis , blobs , that is relatively uniform areas that are smaller than a given size , are identified . typically , the size is measured in terms of pixels of the image size , and a typical size , represented bv a parameter a , may be 500 pixels . thus , a mask is generated of blobs smaller than a ( a = 500 ); a value of 1 is assigned to all pixels outside the blobs , and 0 to all pixels in the blob . the mask thereby produced is referred to as image i 2 . i 2 is logically “ anded ” with i 1 . the values of i av and of σ are recalculated . a focus threshold is computed using f th = i av + c * σ , where c is a constant . a typical value for c is 3 . 5 . then , for all images including the first , the following procedure is carried out . the respective image ( i 1 ) is thresholded using the focusing threshold f th . that is to say 0 is assigned to all pixels below f th , and all other pixels are left unchanged . the new image is referred to hereinbelow as i 3 . a logical and is then carried out of thresholded image i 3 and mask i 2 . the skilled person will appreciate that the order of the thresholding and anding steps may be switched . the result is referred to herein as i 4 . i 4 is cleaned of random noise , preferably by requiring that each pixel in i 4 has at least one non - zero neighbor . such cleaning may be achieved by performing a rank filter on i 4 . the resulting image is referred to herein as i 5 . f = σ all image pixels ( i pixel − i av ) α , where i pixel is the gray level of the pixel in i 5 , and α is a positive number , typically α = 2 . the actual focus position is then taken to be the position corresponding to the image having maximal focus score . filtering for small objects using blob analysis leads to identification of two types of objects , cell objects and non - cell objects . it is possible to filter out the non - cell objects using the following procedure . generally any given slide is likely to have a uniform background color , and it is possible , in a color image , to filter out the background color . in the thresholding stage above , it is possible to carry out thresholding according to color bands and to filter out entirely the color corresponding to the background . such a technique thus ensures that the final image comprises small objects that do not share the non - cell background color , that is to say it includes the objects likely to be of interest to the biologist . for a monochrome image , the filtering out of the background is still possible but is more complex since it has to be based on recognizing uniformity in gray level and texture . as mentioned above , the exposure times during focusing may be considerably lower than the exposure times necessary for achieving a full viewing image . the reduction is due to the procedure above mentioned . an exposure timer may use a predetermined reduced exposure time set at between a fortieth and a third , and preferably between a fifth and a tenth , of the regular exposure time . in a further preferred embodiment of the present invention a fixed ratio between exposure times is dispensed with and instead , image statistics are used to set the exposure times . for example a useful ratio is obtained by taking a typical image snr . an empirically determined snr is defined for a focused image and the ratio between the two is calculated . the square root of the calculated ratio is then used as the ratio between the exposure times . in a further preferred embodiment , the exposure timer may be set such that , in the event of a failure to focus , the focusing exposure time is increased . generally , a characteristic of fluorescent images is a cluster of bright pixels around the region of a positive signal . the above - described use of the rank filter accentuates the characteristic . an image not carrying very much information is unlikely to have pixel clustering and thus the rank filter is liable to remove much of the light in the image , giving such an image a very low focusing score . such a low score may be recognized as a failure to focus , encouraging an increase in focus time as described . on the other hand , in the event of a surfeit of information , the opposite procedure may be followed . with reference now to fig3 , in a preferred embodiment a large difference between the scores of succeeding images in a series is recognized as a sign of having more than sufficient information . thus the apparatus may reduce exposure time . it is appreciated that in using results from images with different exposure times the scores are preferably weighted with a factor to render them comparable . thus if one image has an exposure time of a tenth of a second and the following image is taken using an exposure time of a twentieth of a second , the score of the second image is calibrated so as to be comparable to that of the first image . considering fig3 in more detail , a first image is taken and a focus score is computed . the score is multiplied by a focus factor , currently 1 . a second image is then taken and a score computed . again the score is multiplied by the focus factor which is still 1 . the second score is subtracted from the first score and the result is compared with a threshold gradient grad . if the threshold is exceeded , and the first focus score is larger than a predefined threshold score , a faster exposure time is set and the focus factor is updated to be the ratio between the old and the new exposure times to the power α , wherein α is as defined hereinabove . certain cameras are provided with what is known as a pixel binning feature ( sometimes called also meta - pixel or super - pixel ). the feature takes an internal group of pixels and treats this group as a single pixel . the effect of pixel binning is to decrease resolution and at the same time to increase snr . pixel binning can be helpful in the focusing procedure as outlined above since the resolution has no effect on the above - described focusing procedure , while increased snr may further shorten the exposure times . thus , as long as the pixel binning does not interfere with the identification of large objects then it may usefully be incorporated into the focusing procedure . a simplified embodiment of the present invention may use the detected light level to directly operate the motorized focus 22 in the direction of increasing light level until a peak is determined . in this case , any light meter can be used ( e . g . a photodiode , avalanche photodiode or a photomultiplier ). such a simplified embodiment of the invention is sufficient as long as there are no large objects in the vicinity . thus , in a preferred embodiment , a large object detector , for example the blob analyzer discussed above , may be used as a switch between such a simplified embodiment and an embodiment involving the masking etc procedure outlined above . alternatively switching can be carried out using a low magnification pre - scanner . the low magnification pre - scanner preferably uses a low magnification small na objective lens to produce a pre - scan image , which is then fed to the computer 16 . the computer 16 is able to determine whether large objects are present in the sample , and to select accordingly between the simplified and the more complex embodiments . in one preferred embodiment , the light intensity detection unit is made up of a multi - pixel detector array , for example a 4 × 4 array . using such an array is the equivalent of using ultra - low resolution imaging . the array has the effect of discarding regions where large objects are present , and using information coming only from relevant areas . nevertheless , real - time focusing is still possible . a minimal system may be built from a fluorescent imager that can change the distance between the objective and the sample in a controlled manner . a prototype was built using a zeiss axioplan2 microscope , a sony dxc9000 ccd camera , and a standard general - purpose computer . in order to test the prototype a biological sample was stained with a specific fluorescent dna probe . the computer controls the camera and the distance between the sample and the objective , grabs images from the camera and analyzes the results . a typical focus sequence begins when the computer determines the initial distance z 0 between the objective and the sample . the computer sets the z 0 distance and grabs an image from the camera . the image is analyzed and a focus score f 0 for the current image is computed . the computer than sets another distance z 1 , grabs an image and computes its score f 1 . this sequence is repeated until it is possible to select a position f focus where a peak in the focus score is found , as described above . in a test example to compare the performance of the traditional and the new focus methods , images were taken at different positions , and a focus curve was computed using each method . the sample was a regular blood sample , stained for the sex chromosomes using probes produced by vysis ltd . the final images were taken with an exposure time of 2 seconds . fig5 and 6 show typical focus curves on an image . the focus images when focusing using an embodiment of the invention were taken with an exposure time of 100 msec only , 20 times faster than for the conventional method . reference is now made to fig4 , which is a graph showing a focus curve for the above example using a prior art focusing system . in the graph a focus score produced by the filter , in this case a sobel sharpness filter , is traced against distance from optimal focus . it is noticeable that there is a noticeable peak in the region of − 1 . 5 to 1 . 5 microns from optimal focus , in which the focus score raises from around 900 to around 1000 . outside the above - mentioned region there is very little change in the score . thus the score at 3 microns from optimal focus is practically the same as the score at 2 microns . reference is now made to fig5 , which is a graph showing a focus curve as produced by embodiments of the present invention . in fig5 , again focus score is plotted against distance from optimal focus . this time the focus score in the same region , − 1 . 5 to 1 . 5 microns , varies between 50 and 1000 , which is to say that the discrimination of the system is considerably higher . also , outside the region there are noticeable differences in scores . the score drops between 2 and 3 microns ! reference is now made to fig6 , which shows an image obtained during the focusing process using an embodiment of the present invention . the image that is shown and used is the clearest of the respective set of focusing images . to enable viewing , the gray levels of the original image have been multiplied by 10 . it will be noticed that the image itself has a high level of noise , making standard focusing methods ineffective . there is thus provided , according to the above embodiments , a focusing unit for fluorescent microscopy , which is able to carry out automatic focusing on a high noise image of the kind typical of fluorescent imaging . it is appreciated that features described only in respect of one or some of the embodiments are applicable to other embodiments and that for reasons of space it is not possible to detail all possible combinations . nevertheless , the scope of the above description extends to all reasonable combinations of the above - described features . the present invention is not limited by the above - described embodiments , which are given by way of example only . rather the invention is defined by the appended claims .