turning now to the drawings , wherein the showings are for purposes of illustrating the preferred embodiments of the invention , and not for purposes of limiting same , a hybrid digital screening system is shown in fig2 and is generally designated as 20 . the hybrid digital screening system 20 embodies the recognition that a way to avoid the problem of artifact generation encountered when a hybrid screening system switches between different image characteristic classifications is to control the error propagated to succeeding pixels based on the determined classification of input image segments . in most cases , all the error would be propagated ( as in regular error diffusion ). however , when encountering a transition between high percentage modulation screening to low percentage modulation screening ( i . e . from contone picture to text ), a computational adjustment should be applied to restrict the amount of error diffused . accordingly , the higher the difference in modulation percentage applied to the input data , the greater restriction on the error to be propagated . the hybrid digital screening system 20 receives an input pixel data stream 22 representing an image . the pixel stream 22 can be developed by a scanner or other image producing device , or retrieved from a memory device . the hybrid digital screening system 20 is shown receiving an 8 - bit image , but can be configured to any image input standard . the input pixel stream 22 is received by a segmentation element 24 , which outputs a pixel classification 26 along with the pixel stream 22 . the classification 26 can be envisioned by cross - referencing fig2 and 3 . the image 10 comprises text segments 12 , 14 , contone segment 16 and halftone segment 18 . the segmentation element 24 receives the input video signal 22 , and defines the different segments within the image 10 . thus , segments 12 , 14 are classified as text 30 , 32 ; segment 16 is classified as contone 34 ; and segment 18 is classified as halftone 36 . importantly , the background area 38 is also classified . after segmentation , the pixel stream is selectively rendered based on the classification 26 . referring back to fig2 both the pixel classification 26 and the pixel stream 22 proceed to the screening module 28 . in the screening module 28 the pixel stream 22 is modulated by a screen determined by the pixel classification 26 . for example , a pixel stream classified as continuous tone would likely receive 100 % modulation , while a pixel stream classified as text would likely receive no modulation . the modulated pixel stream is output and referred to as a modified video signal 50 and is output along with the pixel classification 26 to an error diffuser 52 . the error diffuser 52 comprises an adder 54 , a binarization or threshold processor 60 , an error feedback loop 64 , a fractional computer 66 and an error distributor 70 . the adder 54 adds diffused errors 56 from previous pixels to the modified video signal 50 . these diffused errors 56 will be discussed below , but the result out of the adder 54 is known as error diffused video 58 . the error diffused video 58 proceeds to a binarization processor 60 which then produces a digital output video signal 62 which is made by conventional thresholding methods . that is , the value of the input is compared to a threshold and a binary value is output dependent on the comparison . for example , assume 256 possible input values and a threshold of 128 . if the input value is below 128 , then the processor 60 will output a zero . on the other hand , if the input value is greater than or equal to 128 the processor 60 will output a one . as can now be seen , this thresholding induces errors in the output video . using the same example as above , if the input value is 186 , then processor 60 will output a one . this is , however , 70 too dark ( 256 − 186 = 70 ). to account for this error , an error feedback loop is included which subtracts the digital output video signal 62 from the error diffused video 58 resulting in an error value 64 . a fractional computer 66 then provides a fraction of the error value 64 called image context error 68 to error diffusing means 70 which provide the diffused errors 56 to the adder 54 . the fractional computer 66 determines the amount of error propagated to downstream pixels based on the pixel classification 26 . for example , in an area undergoing a high percentage modulation , i . e . a pictorial image , the fractional portion of error value 64 passed through the computer 66 will preferably be 0 %. in a presently preferred embodiment , suitably implemented by the device in fig2 a , the fractional computer 66 comprises a plurality of fractional values in a shift register 68 . in an alternate embodiment , suitably implemented by the device in fig2 b , the fractional computer 66 comprises a full multiplier capable of outputting any fraction of the error value 64 . the image context error 70 then proceeds to an error diffusing means or distributor 72 . referencing fig4 a a sample operation of the error diffuser 72 is shown . an error value 80 is shown in a sample pixel grid and the arrows indicate the selected pixels 82 - 92 which will receive the diffused error . a typical set error diffusion weights is listed in the selected pixels 82 92 . for example , pixel 82 has a fractional value of { fraction ( 8 / 16 )}. in fig4 b a sample propagation resulting from a 50 % weighted look - up table is shown . fig4 c shows the result from a sample 25 % weighted look - up table . fig4 d shows a variable set of error diffusion weights dependent on the classification of the input pixel 26 . it is now apparent that if image context error 70 contains a fractional value of 0 in a variable error diffuser 52 , the error diffusion process is effectively stopped resulting in a pure screened and thresholded output video 62 . [ 0037 ] fig5 shows an alternative embodiment generally designated 94 . the hybrid digital screening system 94 recognizes another way to avoid the problem is to cease downstream error diffusion immediately in certain classifications in addition to either conventional error diffusion or error diffusion as discussed above in reference to fig2 . thus , the system 94 includes an error diffuser 52 identical in all essential respects to that discussed above . additionally , the system 94 includes a bypass binarization module 96 for converting a modified video signal 50 into a bypass digital output video signal 98 . the system 94 then provides the dual outputs , i . e . digital output video signal 62 and bypass digital output video signal 98 to a multiplexer 100 . the multiplexer 100 receives these data streams and outputs one based on the value of the pixel classification 26 . so , for example , pictorial areas the pixel classification 26 would cause the multiplexer 100 to output “ purely screened ” output video 98 . on the other hand , if the value of pixel classification 26 were changing towards text / edge classification , progressively more of the error would be distributed . the parallel computation of error - diffused output 62 and “ purely screened ” output 98 enables the error diffusion circuitry to continuously compute the error generated for each output video , thus preventing artifacts caused by errors diffused from previous pixels ( not just the neighboring pixels ). the invention has been described with reference to the preferred embodiments . potential modifications and alterations will occur to others upon a reading and understanding of the specification . it is our intention to include all such modifications and alterations insofar as they come within the scope of the appended claims , or the equivalents thereof .