as a matter of convenience , when referring to any step in a flow chart , the number of that step will be indicated . fig1 , and 3 use step numbers in the 100 &# 39 ; s , 200 &# 39 ; s , and 300 &# 39 ; s respectively . referring to fig1 step 102 reads , &# 34 ; input corneal video data from u . s . pat . no . 4 , 863 , 260 &# 34 ;. step 103 reads , &# 34 ; find video background intensity limiting search to expected pupil location &# 34 ;. the process executed by these two is advantageously the same as that disclosed in u . s . pat . no . 4 , 863 , 260 . step 104 reads , &# 34 ; find greatest rate of change of video background intensity and set that pixel = actual pupil location &# 34 ;. this box is the basis for fig2 and fig3 below . the output of the pupil location data to display is output in step 105 . in step 106 the detection angle is incremented after which step 107 determines whether all radial pupil positions , illustratively 256 in number , have been determined . if not , steps 101 through 107 are repeated . in general , a decision is made as to where the pupil radius is expected to be located . to speed up processing , the range of locations at which the pupil is likely to occur are used in the calculations . then , for each one of the 256 radial scans , the data obtained is examined to determine the greatest rate of change in background intensity over the expected range . it has been determined that the greatest rate of change in background intensity occurs where the background changes from the darkness of the pupil to the relative lightness of the iris regardless of the actual iris color . even in the case of a dark brown iris , the rate of change in background intensity is still greatest where the pupil meets the iris . the pixel containing the greatest rate of change is found by examining eight pixels to the left and to the right of the pixel under examination . if the rate of change in background intensity varies little over this seventeen pixel range , then the pixel under examination is not the pixel containing the greatest rate of change . the next pixel is then examined and the procedure repeats itself until the rate of change is maximized . the pixel where the greatest rate of change is found is the pixel containing the location of the pupil . referring now to fig2 and to fig3 these general principles are explicitly displayed . the raw data values [ called rdvs ] of pixels in all 256 radial slices are loaded into an array , step 202 . pixels are picture elements or points containing a numerical value representing the average brightness of an image over the area that the pixel subtends on the original continuous image . raw data values refer to the signal obtained by prior u . s . pat . no . 4 , 863 , 260 , represented pixel illumination intensity . pixel illumination intensity is the intensity or brightness of the videographed subject as recorded and digitized by measuring the voltage at closely spaced intervals along each video camera scan line . an accumulator is initialized to 0 as well as two arrays , &# 34 ; background &# 34 ; and &# 34 ; topology &# 34 ;, step 203 . an accumulator is a temporary computer memory address where numbers are totaled or stored . background refers to the background signal that is a part of the raw data value input signal . topology refers to the other part of the raw data value input signal and , when analyzed in accordance with prior u . s . pat . no . 4 , 863 , 260 , yields the topological configuration of the corneal exterior surface . it is this background signal that contains the information yielding the pupil outline . a range of pixels is selected contained the range of pixels for the pupil location [ called pupilrange ] as well as additional pixels on either side necessary for image processing ; all other pixels are ignored , step 204 . then a filter range [ called filterrange ] is selected , step 204 . filters are mathematical constructs that produce modified images emphasizing some aspect of the original image at the expense of others . a pixel is examined to determine if it is the first in the selected image processing range , step 205 , and , if so , the first accumulator is loaded with all rdvs for pixels in filterrange , step 206 . if not , the accumulator needs not be loaded but must be updated but subtracting the value of the first pixel in filterrange and adding the value of the first pixel after filterrange , step 207 . this would effectively &# 34 ; slide &# 34 ; the filter over the image processing range , one pixel at a time . the image processing is continued by selecting the pixel in the center of filterrange , and , for that pixel , setting background equal to the average pixel illumination intensity over the filter range and solving for topology by subtracting background from the rdvs , step 208 . then , for the pixel currently under examination ( as opposed to the one at the center of the filter ), background is set to the background as calculated for the pixel at the center of the filter plus the topology divided by the number of pixels in filterrange , step 209 . an array contained data regarding pupil outline [ called , pupil ] initialized to 0 , step 210 , and the pupil outline is extracted from background , steps 211 and 301 . a range of pixels over which the pupil can be selected is determined [ called , pupilrange ] and all out of range pixels are ignored , step 302 . a pixel is examined to determine if it is the first in pupilrange , step 303 , and , if so , a second and third accumulator are initialized , step 304 , the second accumulator is set to the negative of the combined backgrounds of n pixels , step 305 , and the third accumulator is set to the combined backgrounds of the following n pixels , step 306 . if not , the second accumulator has added to itself the background of the previous pixel minus that of the pixel n pixels ahead , step 307 , and the third accumulator subtracts from itself the combined backgrounds of the n pixels following the first set of n pixels , step 308 . finally , the array pupil is set for the pixel n pixels ahead of the current pixel to the combined values of the second and third accumulators , step 309 . if pupil is not yet filled for all 256 slices , step 310 , the procedure loops back until it is , step 311 . if it is filled , it is then analyzed in the pupilrange , step 312 , for greatest rate of change in background intensity by incrementing the search pixel by pixel unto the value in pupil for the pixel under evaluation is greater than the values in pupil for the pixels eight pixels to the left and right , step 313 . this pixel representing the greatest rate of change in background intensity identifies the pupil position . the entire process repeats itself should another exam be required , step 314 . referring to fig4 the data appears as an asymmetric ring ( unless the pupil is perfectly symmetrical ) superimposed on the output already disclosed by the &# 39 ; 260 patent . the &# 39 ; 260 output is , mainly , a color scale map of dioptric powers of the cornea . no pupil location is shown . now , in accordance with my invention , the location of the pupil is precisely calculated and reflected on the color scale corneal map . this precise location of the pupil , manifested by the asymmetrical white ring on the color scale , is intended to enhance an ophthalmic surgeon &# 39 ; s ability to correctly decide upon an appropriate course of action . referring now to fig5 the graph plots distance from the center of the eye versus video amplitude of the signal received as disclosed by patent no . &# 39 ; 260 . in the &# 39 ; 260 patent , the signal &# 39 ; s background intensity is zeroed out and discarded as unused information . the present invention utilizes this background signal which contains information necessary to find the pupil outline . fig5 is a graph of the raw data before this invention begins its major tasks . referring now to fig6 the graph plots the raw data as it appears after it has been low pass filtered . the low pass filtering separates the background signal from the raw data . it is this signal that is analyzed for the said maximum rate of change . fig7 is a graph of the filtered data showing the greatest rate of change along the expected distances . the point at which the rate of change is greatest is seen where the graph changes path . this location is that which is stored in an array for later plotting as described above .
method for accurately displaying the location of the pupil perimeter on a corneal topography map such as is disclosed in the prior art gersten et al ., u . s . pat . no . 4 , 863 , 260 . in the process of deriving such topographic information , the process disclosed in that patent obtained a two - dimensional video image of the cornea . in the method of the present invention , the background illumination of the video image is sampled and the video signal is corrected for the effects of camera distortions , artifacts , and specular glare . the corrected data is analyzed and the point at which the greatest rate of change in background illumination occurs is determined to be a point on the periphery of the pupil . the peripheral points so determined are then displayed in superposition to the corneal topographic map thereby indicating the pupil outline .