CROSS REFERENCE TO RELATED APPLICATIONS 
     This application claims priority to provisional application No. 61/191,414, filed Sep. 8, 2008, which is incorporated herein, in its entirety, by reference. 
    
    
     FIELD OF THE INVENTION 
     The present invention relates to a method of assigning predetermined adjustment curves to correct for dot gain to achieve accurate print quality as well as accurate color management. 
     BACKGROUND OF THE INVENTION 
     In monochrome half-tone image reproduction, various shades appearing in a continuous tone original image are reproduced on paper by a single tone ink. To simulate the multiple tones in the original, the continuous tone image is converted into a half-tone image comprising a plurality of different size dots of a uniform optical is density level, as is well known in the art. Also, as is well known in the art, color images are printed using 4-color separations, where each pixel of a digital image corresponds to a combination of color and intensity represented on each of the 4 color separations. Thus, each pixel in the digital image corresponding to one of these separations is then translated into a specified dot size on a printing plate to be used for that color. The conversion of color intensity to dot size is typically represented by a generic transfer curve that takes the input of desired color tone and converts it to desired dot size in the imagesetter. Such a transfer curve may be linear (i.e. a 20% color tone equates to a dot that is 20% of the maximum dot size, and a 70% color tone equates to a dot that is 70% of the maximum dot size), or may be a curve that corresponds to some other mathematical function. 
     Printing of digital images is typically complicated by the phenomenon of “dot gain,” in which the size of printed halftone dots is larger than that specified by the digital image file employed by the imagesetter. Dot gain interferes with the ability to produce similar standardized colors between printing press runs. To compensate for this effect, historically, printing press users entered in specific X and Y transfer coordinates, representing on the X-axis the desired color density, expressed as a percentage of maximum color tone, and on the Y-axis, the actual color density setting (i.e. printing plate dot size) used to produce the desired color output, as depicted in  FIG. 8 . This practice evolved into the generation and application of press adjustment transfer curves by mathematically fitting the curve to a set of experimentally derived points, as shown in  FIG. 9 . Each adjustment curve is a mathematical function specifying the required dot size on the printing plate to compensate for on-press dot gain, thus resulting in a calibrated plate. The adjustment curve thus represents mapping of an input color percentage to a desired output dot size on the printing plate to produce the desired result, taking into account dot gain. Between press runs, there may be a great deal of variation. These variations depend on numerous press factors (press type, ink type, speed, paper type) as well environmental factors (temperature, humidity, etc.). As some of these conditions may change during or between press runs, the ideal press adjustment curve may change as well. 
     Traditionally, little has been done to correct dot gain in offset printing, because of the limited dot gain that occurs. As new printing methods have become the industry standard, however, dot gain has become an increasingly larger problem. For example, dot gain in flexographic printing may be much greater than in offset printing, requiring the use of press adjustment curves. Even in offset printing, the use of new screening technologies such stochastic screening and concentric screening have necessitated the use of adjustment curves. In many cases, users create and apply new custom curves whenever the printed image begins to deteriorate. Historically, users created custom curves for each press. These custom curves could vary from user to user and were often based on time-consuming and expensive test runs. The number of custom curves created by users has often become unmanageable, because of the number of factors and variables involved. Creation of numerous custom curves may lead to more costly, time-consuming, and laborious adjustments if the wrong curve is applied. Because it may cost thousands of dollars to create a standard press run, it can be cost- and time-prohibitive to perform numerous standard press runs. 
     Therefore, a system is needed that can quickly take the information from a current press run and determine the optimum adjustment curve. A system is also needed that can bring organization to the curve selection process, instead of the chaos of numerous unsynchronized custom curves. 
     SUMMARY OF THE INVENTION 
     One embodiment of the invention comprises a method for adjusting color tones of an input digital image file to create an adjusted digital image file. The method comprises providing a plurality of predetermined curves, each curve specifying an adjusted color tone percentage output as a function of input color tone percentage over a range of input and output values. Each curve also reflects a midpoint magnitude and contrast over the range of input and output values, where the midpoint magnitude comprises the adjusted color tone percentage output corresponding to an input color tone percentage of 50%. The individual curves each represent a combination of midpoint magnitude and contrast that is different from the combination for any other curve in the plurality of curves. From an input of at least two data points, each data point comprising an adjusted color tone percentage output corresponding to an input color tone percentage, the method comprises selecting a curve by determining which one of the plurality of predetermined curves most closely matches the data points. The selected curve is applied to the input digital image file to produce the adjusted digital image file. 
     Some embodiments of the invention further comprising producing a printed image or a printing plate from the adjusted digital image file. In some embodiments of the invention, the plurality of curves comprise multiple families of curves, each family of curves comprising a plurality of member curves identified by a midpoint magnitude of the curve. 
     Another embodiment of the invention comprises a computer programmed with instructions for adjusting color tones of an input digital image file to create an adjusted digital image file. The computer comprises a means, such as but not limited to a computer memory or other media for storing information, for storing a plurality of predetermined curves, each curve specifying an adjusted color tone percentage output as a function of input color tone percentage over a range of input and output values. Each curve reflects a midpoint magnitude and contrast over the range of input and output values and represents a combination of midpoint magnitude and contrast that is different from the combination for any other curve in the plurality of curves. The programmed computer further comprises means, such as any user interface known in the art, for receiving an input of at least two data points. Each data point comprises an adjusted color tone percentage and an input color tone percentage. The programmed computer further comprises means, such as a computer processor, for determining which one of the plurality of stored predetermined curves most closely matches the two or more data points. The programmed computer further comprises means, such as the same or another computer processor, for applying the selected curve to the input digital file to produce the adjusted digital image file. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The invention is best understood from the following detailed description when read in connection with the accompanying drawings. It is emphasized that, according to common practice, various features/elements of the drawings may not be drawn to scale. On the contrary, the dimensions of the various features/elements may be arbitrarily expanded or reduced for clarity. Moreover, in the drawings, common numerical references are used to represent like features/elements. Included in the drawing are the following figures: 
         FIG. 1  is an exemplary view of a table of 408 identifiers for pre-press curves in accordance with an exemplary embodiment of the present invention; 
         FIG. 2  is a graph of an exemplary curve identified as E 42 ; 
         FIG. 3  is a graph of two exemplary curves identified as E 35  and E 42 ; 
         FIG. 4  is a graph of two exemplary curves identified as C 42  and E 42 ; 
         FIG. 5A  is a graph of eight exemplary curves identified as A 50 , B 50 , C 50 , D 50 , E 50 , F 50 , G 50  and H 50 ; 
         FIG. 5B  is a graph of eight exemplary curves identified as A 40 , B 40 , C 40 , D 40 , E 40 , F 40 , G 40  and H 40 ; 
         FIG. 5C  is a graph of eight exemplary curves identified as A 30 , B 30 , C 30 , D 30 , E 30 , F 30 , G 30  and H 30 ; 
         FIG. 6  is a graph of eleven exemplary curves identified as E 20 , E 25 , E 30 , E 35 , E 40 , E 45 , E 50 , E 55 , E 60 , E 65  and E 70 ; 
         FIG. 7A  is a graph of seven exemplary 10% derivative curves; 
         FIG. 7B  is a graph of seven exemplary 75% derivative curves; 
         FIG. 8  depicts a series of X-Y points of a calibration curve plotted according to experimental results, in accordance with the prior art; 
         FIG. 9  depicts a curve mathematically fit to experimental results in accordance with the prior art; and 
         FIG. 10  depicts a predetermined curve matched to experimental results such as in accordance with the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     The inventor has found that, with an average of 8% variation within a press sheet and even more variation between press sheets, making and altering custom curves actually increases the variation measured on press. The present invention provides methods of dealing with this issue by obviating the need for custom curves. 
     The invention provides a system of predetermined, synchronized press adjustment curves designed to eliminate the problems associated with creating and maintaining custom curves. After taking a limited number of data points from the printed materials, the system enables selection of a press compensation curve that adjusts for the variables associated with a particular set of press conditions. While it is possible to exactly fit a curve to any limited number of data points, the mechanism of this invention is to match a pre-determined curve to the limited number of data points. In this regard, the invention relates to curve matching, as shown in  FIG. 10 , not curve fitting as shown in  FIG. 9 . 
     Each pre-determined curve relates to a contrast profile and a midpoint magnitude value. In the exemplary embodiment described herein, each curve is given an alphanumeric identifier that is reflective of the contrast profile family and midpoint magnitude value. In the exemplary embodiment shown in  FIG. 1 , the curve set comprises eight contrast profile families (A-H, with H being highest contrast) and 51 midpoint magnitude values (20-70, with 70 being highest midpoint magnitude). Thus, for the embodiment shown in  FIG. 1 , there are 408 pre-determined curve choices, representing all combinations of the letters A-H and the numbers 20-70. Although this example uses eight letters and 51 numbers, the invention is not limited to use of only numbers or letters, nor the use of only eight contrast profile families and 51 midpoint magnitude values. Larger or smaller selection ranges for contrast and midpoint magnitude may be used. 
     Typically, at least three contrast profile families and more typically at least five contrast profile families are provided. If the range of contrast profile families exceeds 26, designations such as AA and AB, etc. may be used in a letter-based nomenclature. Typically, no more that 50 contrast profile families are used, and more typically no more than 20 contrast profile families or, ideally, no more than 10 contrast profile families. The same applies for the range of midpoint magnitude numbers to be used. Although the exemplary embodiment discussed herein includes member curves representing midpoint magnitudes for all integers in the range from 20 to 70, the range may have at its lower limit any number greater than zero, and as its upper limit any number less than 100, and less than all of the integers in the range (or non-integers in the range) may be included. Typically the number of curves is selected to provide a spread of curves that will provide a curve with acceptable tolerances to compensate for any set of press conditions. In the exemplary embodiment described herein, the curve set consists of 408 curves. 
     The contrast profile families of curves (A-H) are characterized by different shapes and slopes. The system is designed to provide a sufficient variety of curve shapes to cover most conceivable printing conditions. 
       FIG. 2  shows an example of the pre-press curve that has been assigned the identifier of E 42 . E 42  is a medium contrast curve (near the middle of the letters between A-H) with the magnitude at 50% on the X-axis (50% desired color density), referred to herein as the midpoint magnitude, corresponding to 42% on the Y-axis (dot-size reduced on the printing plate to 42% of the maximum).  FIG. 3  shows an exemplary embodiment of curves E 35  and E 42 , demonstrating that E curves have essentially the same general shape, but with the 50% value mapping to different Y-values consistent with the numerical nomenclature.  FIG. 4  shows an exemplary embodiment of curves C 42  and E 42 , showing that the shape and slope of the two curves varies between the C curve shape and the E curve shape, but that because both curves have a midpoint magnitude of 42, both are anchored at X-Y coordinate of 50,42.  FIGS. 5A through 5C  show the varying shapes and slopes of curves A through H at magnitudes of 50, 40 and 30 respectively. Furthermore,  FIG. 6  shows an exemplary E curve at 5% midpoint magnitude intervals ranging from a minimum midpoint magnitude of 20% to a maximum midpoint magnitude of 70%. 
     The curve set consists of a series of curves created from a fourth order polynomial of the form:
 
 Y=bx+cx   2   +dx   3   +ex   4  
 
A constant is not provided because the Y intercept for each curve is always 0. Each curve is fit to five points, x=0%, x=10%, x=50%, x=75% and x=100%. The values of Y at x=0% and x=100% are always anchored at 0% and 100% respectively. In the exemplary embodiment, the 50% value determines the numerical value of the alphanumeric identifier. For example, on the E 42  curve shown in  FIG. 1 , entering x=50% into the fourth order polynomial gives Y=42%. The x=10% and x=75% values determine the shape and slope of the curve as further described below.
 
     A 10% derivation function expresses the Y value of a curve as a function of the midpoint magnitude for that curve. Similarly, the 75% derivation function expresses the Y value of a curve as a function of the midpoint magnitude for that curve. The derivation functions themselves are second order polynomials of the format:
 
 Y=k   1   x   2   +k   2   x+C  
 
evenly spaced between the A through H curves, wherein in the exemplary embodiment, k 1 , k 2 , and C are as shown in Tables 7A and 7B.  FIG. 7A  and  FIG. 7B  are exemplary graphical representations of curves calculated by an exemplary 10% derivation function and an exemplary 75% derivation function, respectively.
 
     Thus, for example, in one exemplary embodiment, the 10% value for the D 40  curve is generated by plugging 40% into the above polynomial using the coefficient and constant values for k 1 , k 2 , and C as provided for the D family in Table 7A, and the 75% value for the D 40  curve is generated by plugging 40% into the above polynomial using the coefficient and constant values for k 1 , k 2 , and C as provided for the D family in Table 7B. 
     
       
         
               
             
               
               
               
               
               
             
               
               
               
               
               
             
           
               
                 TABLE 7A 
               
             
             
               
                   
               
               
                 10% Derivation Function Coefficients and Constant 
               
             
          
           
               
                   
                 Curve 
                   
                   
                   
               
               
                   
                 Family 
                 X 2   
                 X 
                 C 
               
               
                   
                   
               
             
          
           
               
                   
                 A 
                 0.1296 
                 0.1967 
                 0.0168 
               
               
                   
                 B 
                 0.1556 
                 0.1611 
                 0.0146 
               
               
                   
                 C 
                 0.1852 
                 0.1204 
                 0.0135 
               
               
                   
                 D 
                 0.2148 
                 0.0796 
                 0.0125 
               
               
                   
                 E 
                 0.2444 
                 0.0389 
                 0.0114 
               
               
                   
                 F 
                 0.2667 
                 0.0067 
                 0.0080 
               
               
                   
                 G 
                 0.2963 
                 −0.0341 
                 0.0070 
               
               
                   
                 H 
                 0.3259 
                 −0.0748 
                 0.0059 
               
               
                   
                   
               
             
          
         
       
     
     
       
         
               
             
               
               
               
               
               
             
               
               
               
               
               
             
           
               
                 TABLE 7B 
               
             
             
               
                   
               
               
                 75% Derivation Function Coefficients and Constant 
               
             
          
           
               
                   
                 Curve 
                   
                   
                   
               
               
                   
                 Family 
                 X 2   
                 X 
                 C 
               
               
                   
                   
               
             
          
           
               
                   
                 A 
                 −0.2889 
                 1.3322 
                 0.1046 
               
               
                   
                 B 
                 −0.3407 
                 1.3519 
                 0.1193 
               
               
                   
                 C 
                 −0.3852 
                 1.3630 
                 0.1358 
               
               
                   
                 D 
                 −0.4296 
                 1.3741 
                 0.1524 
               
               
                   
                 E 
                 −0.5037 
                 1.4126 
                 0.1646 
               
               
                   
                 F 
                 −0.5333 
                 1.4133 
                 0.1817 
               
               
                   
                 G 
                 −0.5778 
                 1.4244 
                 0.1982 
               
               
                   
                 H 
                 −0.6222 
                 1.4356 
                 0.2149 
               
               
                   
                   
               
             
          
         
       
     
     The 408 press curves are derived, such as by a programmed computer by first calculating the 10% and 75% values using the 10% and 75% derivation functions for the selected curve family (such as A through H) for each member curve (for example 20 through 70). Next, the fourth order polynomial is mathematically exactly fit to the five standard points (x=0%, x=10%, x=50%, x=75% and x=100%) defined by the combination of boundary conditions (0,0 and 100,100), the given parameter X=50, Y=midpoint magnitude of the curve, and derived points from the 10% and 75% derivation functions as described above. The algorithms, including software for programming a computer to use such algorithms, required for deriving the fourth order polynomials to fit 5 points, such as least squares regression analysis, are well known. Using the fourth-order polynomials so derived, any point along the curve can then be calculated. 
     There are numerous ways to find the right curve to apply for a given set of conditions. One way to select a curve is to match any specification, including GRACoL G7 GRACoL 7, SWOP, or other specification designed by the user. The user can also take a custom curve with a plurality of x, y value data points made from any other system such as IdeaLink™, sold by IDEAlliance of Alexandria, Va., and, using appropriate software, find the closest curve from a plurality of synchronized curves in accordance with this invention. The algorithms, including software for programming a computer to use such algorithms, for matching existing curves to a limited set of points or to another curve are known. Such algorithms may simply check all available curves compared to the data, calculate the deviation between each point and the curves for all of the available curves, and select the one with the least total deviation as the closest match. Such algorithms may, for example, quantify the deviation in terms of absolute value or in terms of the squared difference, but the invention is not limited to any particular algorithm. 
     Another way to select a curve is for the user to print a target, such as EskoArtwork&#39;s Universal 4c Target™, and find the best curve match with associated software, such as EskoArtwork FastMatch™ software. Through as few as eight measurements, the user can find the best curve from any set of predetermined curves, such as a set of synchronized curves in accordance with the invention, for each of the four (or more) process colors. The curve thus identified can be directly input into associated software, for example that provided with EskoArtwork&#39;s Nexus™ software package. In the exemplary embodiment, the set of pre-determined curves is logical and therefore can be averaged by both variables, and the curves are naturally biased, such that the difference in contrast families is slightly larger than the difference between curve magnitudes so that curves for different colors (C, M, Y, and K) are likely to have the same contrast even if they have different magnitudes. This is consistent with industry findings that it is more important to have the color “balanced” than to have it be the exactly correct “lightness”. 
     On-Going Curve Adjustment 
     A significant advantage of using standard curves according to the invention is the simplicity of making on-going curve adjustments. If presses are regularly printing too lightly, the operator may merely increase the curve number corresponding to a higher midpoint magnitude. If the contrast is too high, the operator may decrease the curve letter. Assessments can be made visually or quantitatively through measurement of the press control strip. All the user needs to know is the standard curve used for the job. If the user has data from multiple press runs, it may be useful to average them together. While normal curves may be difficult to average, the task is easy with the predetermined curves according to the invention. For example, the average of D-43 and F-37 is E-40. Thus, the methods of this invention, and associate nomenclature simplify curve averaging and adjustment. 
     Improve Color Management 
     The methods of this invention may be used either “stand-alone” or to complement color management. International Color Consortium (ICC) profiles are more accurate when the correct curves are applied to the press ICC profile test run. What&#39;s less commonly known, however, is that if press conditions change, the ICC profiles must typically be re-made. The use of pre-determined curves according to the invention eliminates this need. Through the use of conversion curves, an ICC profile can be edited in minutes to accommodate a change in press conditions, thereby minimizing on-press testing. For example, if press testing is done using an E 42  profile, the user might, upon evaluating the run, conclude that an E 35  profile would have been better. By mathematically generating a conversion curve that accounts for the differences between E 42  and E 35 , the ICC profile can be adjusted so as to be a proper match for running under E 35  conditions, without having to make actual test press runs under those conditions. 
     In one exemplary embodiment, to achieve proper color management if there is an advanced screening, a user may conduct a single color test. The user may then properly calibrate the plate using standard plate calibration programming. Next the user may run a 4c test to further determine the accuracy of the color. Finally, to achieve maximum color accuracy the user can run an ICC profile target and make ICC profiles. 
     Control Theory for Press Operation 
     Using synchronized curves such as those of the present invention facilitate the use of proper control theory with respect to a printing operation as a whole. A press operator using synchronized curves and measuring every plate and every press run to provide feedback, can make minimal adjustments by selecting curves from the families of curves that are only slightly varied (typically only in magnitude) from those previously used, only when the actual results exceed some threshold window of acceptability. Thus, instead of press operators constantly choosing different unsynchronized or “custom” pre-press curves representing exact mathematical fits of actual data, which can introduce more variability, press operators can choose different curves within a same family of curves, thereby introducing only small perturbations in the system. 
     It should be understood that a computer may be specifically programmed with specific instructions, such as through software, to carry out some or all of the method steps of this invention. This specifically programmed computer may be integrated with a printing press or imagesetter for storing the predetermined synchronized curves, selecting the predetermined curve that is a best fit to a set of data, and applying the selected curve to the digital image prior to sending the image to an imagesetter for making plates usable by the printing press. The integration with an imagesetter and/or printing press may be over communication links, or a physical integration. 
     Although the invention is illustrated and described herein with reference to specific embodiments, the invention is not intended to be limited to the details shown. Rather, various modifications may be made in the details within the scope and range of equivalents of the claims without departing from the invention.
A method for adjusting color tones of an input digital image file to create an adjusted digital image file. A plurality of predetermined curves are provided, each curve specifying an adjusted color tone percentage output as a function of input color tone percentage and representing a combination of midpoint magnitude and contrast different than for any other curve. The method comprises selecting a curve by determining which one of the plurality of curves most closely matches at least two data points. The selected curve is then applied to the input digital image file to produce the adjusted digital image file.