Method for determining scan line misalignments

Abstract

A test image has a black bias on a white background. The black bias is a line set at about 45 degrees to the scan lines of a scanner. Boundary points of the scanned bias are found. A regression line is calculated from the positions of the boundary points. Differences in the positions of adjacent boundary points, together with the slope reciprocal of the regression line, are used to determine error values. The error values are compared with a gate value to determine if there are any occurrences of scan line misalignment.

1. A method for determining if an image from a scanner has an occurrence of scan line misalignment, the scanner comprising a housing, a scanning platform upon which is placed a document to be scanned, a scanning module to scan the document, and a driving module to drive the scanning module, the method comprising:
 scanning a document having a test image and collecting corresponding scan line image information from a plurality of scan lines in order, each scan line image having a portion of the scanned image of the test image;  
 using a method of searching for a predetermined boundary point to find the position of a boundary point of the test image from the information in every scan line image;  
 calculating a regression line from the position of the boundary point;  
 calculating discrepancies of corresponding positions of boundary points and the slope reciprocal of the regression line from the image information of adjacent scan lines and determining corresponding error values from every discrepancy and slope reciprocal; and  
 comparing every error value with a predetermined gate value to determine if the scan line images from the scanner have any occurrences of scan line misalignment.  
 
     
     
       2. The method of  claim 1  wherein the method uses all found positions of the boundary points to calculate the regression line. 
     
     
       3. The method of  claim 1  wherein the method uses a portion of the found positions of the boundary points to calculate the regression line. 
     
     
       4. The method of  claim 1  wherein the regression line y=mx+b is calculated by 
         m   =             ∑   n       i   =   1       ⁢       x   i     ⁢     y   i         -       (         ∑   n       i   =   1       ⁢     x   i       )     ⁢     (         ∑   n       i   =   1       ⁢     y   i       )             n   ⁢         ∑   n       i   =   1       ⁢     x   i   2         -       (         ∑   n       i   =   1       ⁢     x   i       )     2           ,     b   =           (         ∑   n       i   =   1       ⁢     y   i       )     ⁢     (         ∑   n       i   =   1       ⁢     x   i   2       )       -       (         ∑   n       i   =   1       ⁢     x   i       )     ⁢     (         ∑   n       i   =   1       ⁢       x   i     ⁢     y   i         )             n   ⁢         ∑   n       i   =   1       ⁢     x   i   2         -       (         ∑   n       i   =   1       ⁢     x   i       )     2               
 
       andwherein (x i , y i ) are the positions of the boundary points chosen to calculate the regression line. 
     
     
       5. The method of  claim 1  wherein the document has a white background, and the test pattern is a black bias from an upper-right position to a lower-left position, each scan line comprising gray-scale image information from a plurality of pixels, and the method of searching for a predetermined boundary point proceeds from up to down and from left to right to search for the boundary points of the bias from the gray-scale image information in each scan line. 
     
     
       6. The method of  claim 5  wherein the method of searching for a predetermined boundary point has the following steps  comprises:
 averaging the gray-scale values of a plurality of pixels in a chosen white region of a scan line, half of the averaging result being a boundary reference level (V P1 ), and defining the gray-scale value of a pixel closest to the boundary referencing level as a first boundary reference point (P 1 );  
 moving forward a first predetermined number of pixels from the first boundary reference point to select a second predetermined number of pixels, the average of the gray-scale values of the second predetermined number of pixels being a white reference level (V W );  
 moving backward the first predetermined number of pixels from the first boundary reference point to select the second predetermined number of pixels, the average of the gray-scale values of the second predetermined number of pixels being a black reference level (V B );  
 averaging the white and the black reference levels to determine a boundary level (V 0 );  
 searching for two adjacent pixels (P 2 , P 3 ) from the plurality of pixels of the scan lines where the boundary level between both gray-scale values of the two adjacent pixels satisfies (V P2 ≦V 0 ≦V P2 ), and setting these two pixels as a second and a third boundary reference point (P 2 , P 3 ); and  
 using the gray-scale values of the second and the third reference points (V P2 , V P3 ) and the boundary level (V 0 ) to calculate the boundary point (X) mathematically by 
       x   =       P   2     +           V     p   ⁢           ⁢   2       -     V   0           V     p   ⁢           ⁢   2       -     V     p   ⁢           ⁢   3           .           
 
 
     
     
       7. The method of  claim 6  wherein the first and the second predetermined numbers are both 15. 
     
     
       8. The method of  claim 1  wherein the width of the black bias is 2 mm, and the black bias has an angle of about 45 degrees with respect to the scan lines. 
     
     
       9. The method of  claim 1  wherein the predetermined gate value is 0.3. 
     
     
       10. A method for identifying scan line misalignment in a scanner, comprising:
   scanning a test image to obtain scanned image data corresponding to a plurality of scan lines of the scanner;        locating one or more boundary points of the scanned test image corresponding to at least a portion of the plurality of scan lines;        determining a regression line for at least a portion of the one or more boundary points;        determining a corresponding error value for at least a portion of the one or more boundary points, based at least in part on the regression line;        comparing one or more corresponding error values with a gate value; and        determining whether the scanner has a scan line misalignment based at least in part on the comparing.     
     
     
       11. The method of  claim 10 , wherein locating one or more boundary points further comprises:
   for a particular scan line, identifying a first boundary reference point V   P   ;        determining a white reference level V   W   ;        determining a black reference level V   B   ;        averaging the white and the black reference levels to determine a boundary level V   0   ;        selecting two pixels as a second and a third boundary reference point P   2    and P   3    that satisfy the relationship V   P3   ≦V   0   ≦V   P2   , wherein V   P2    and V   P3    comprise second and third boundary reference points; and        calculating a boundary point  ( x )  mathematically by          x   =       P   2     +           V     p   ⁢           ⁢   2       -     V   0           V     p   ⁢           ⁢   2       -     V     p   ⁢           ⁢   3           .               
       
        
       
     
     
       12. The method of  claim 10 , wherein determining a corresponding error value includes:
   determining a difference in position between a boundary point corresponding with a first scan line and a boundary point corresponding with a second scan line;        determining a reciprocal of the slope of the regression line at the first scan line; and        determining an error value corresponding with the first scan line based at least in part on the difference between the determined difference in position between the boundary point corresponding with the first scan line and the boundary point corresponding with the second scan line and the determined reciprocal of the slope of the regression line at the first scan line.     
     
     
       13. The method of  claim 12 , wherein the first and second scan lines comprise adjacent scan lines. 
     
     
       14. The method of  claim 10 , wherein the gate value comprises a predetermined value. 
     
     
       15. The method of  claim 10 , wherein the gate value is determined based on properties of the scanner. 
     
     
       16. The method of  claim 10 , wherein determining whether the scanner has a scan line misalignment includes identifying a misalignment if the error value is numerically greater than the gate value. 
     
     
       17. A scanner having a plurality of scan lines, the scanner comprising:
   a housing;        a scanning platform positioned at least partially in the housing;        a scanning module positioned at least partially in the housing and configured to obtain a scanned image of the document; and        a driving module positioned at least partially in the housing and configured to drive the scanning module to scan a document positioned on the scanning platform, wherein the scanner is configured to—locate one or more boundary points of the scanned image;        determine a regression line for at least a portion of the one or more boundary points;        determine corresponding error values for the one or more boundary points, based at least in part on the regression line; and        compare one or more corresponding error values with a gate value.     
     
     
       18. The scanner of  claim 17 , wherein said driving module is further configured to identify a misalignment if the error value is numerically greater than the gate value. 
     
     
       19. The scanner of  claim 17 , wherein said document comprises an image of a test pattern. 
     
     
       20. The scanner of  claim 19 , wherein said image of a test pattern comprises a black bias that runs from the upper- right portion of the document to the lower - left portion of the document.   
     
     
       21. The scanner of  claim 17 , wherein said scanner is further configured to:
   identify a first boundary reference point V   P    for a particular scan line;        determine a white reference level V   W   ;        determine a black reference level V   B   ;        average the white and the black reference levels to determine a boundary level V   0   ;        select two pixels as a second and a third boundary reference point P   2   , and P   3    that satisfy the relationship V   P3   ≦V   0   ≦V   P2   , wherein V   P2    and V   P3    comprise second and third boundary reference points; and        calculate a boundary point  ( x )  mathematically by          x   =       P   2     +           V     p   ⁢           ⁢   2       -     V   0           V     p   ⁢           ⁢   2       -     V     p   ⁢           ⁢   3           .               
       
        
       
     
     
       22. The scanner of  claim 17 , wherein said scanner is further configured to:
   determine a difference in position between a boundary point corresponding with a first scan line and a boundary point corresponding with a second scan line;        determine a reciprocal of the slope of the regression line at the first scan line; and        determine an error value corresponding with the first scan line based at least in part on the difference between the determined difference in position between the boundary point corresponding with the first scan line and the boundary point corresponding with the second scan line and the determined reciprocal of the slope of the regression line at the first scan line.