Abstract:
Using methods, computer-readable storage media, and apparatuses for computer-implemented processing, a passage of text may be variably rendered. For each glyph in the passage of text, a glyph representation is varied according to a geometric transformation that was determined from statistical measurements of at least one geometric property from an ensemble of representations of the current glyph. Each varied glyph representation is included in renderable output data, such that when the passage of text is rendered to an output device, a given rendered representation of a given glyph subtly differs from other rendered representations of the given glyph.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application is a continuation of U.S. patent application Ser. No. 12/756,970, filed Apr. 8, 2010, titled “VARIABLE GLYPH SYSTEM AND METHOD,” naming inventors Eloise Bune D&#39;AGOSTINO, Michael Bennett D&#39;AGOSTINO, Bryan Michael MINOR, Tamas FRAJKA, and Michel Francois PETTIGREW; and filed under Attorney Docket No. GRAC-2010006. Prior application Ser. No. 12/756,970 claims the benefit of priority to U.S. Provisional Application No. 61/167,768, filed Apr. 8, 2009; titled “WORD SEGMENTATION SYSTEM AND METHOD”; naming inventors Eloise Bune D&#39;AGOSTINO, Michael Bennett D&#39;AGOSTINO, Bryan Michael MINOR, Tamas FRAJKA, and Michel Francois PETTIGREW; and filed under Attorney Docket No. GRAC-2009003. The above-cited applications are incorporated herein by reference in their entireties, for all purposes. 
     
    
     FIELD 
       [0002]    The present invention relates to computer handwriting analysis and synthesis, and in particular to methods for automatic word segmentation and glyph variation. 
       BACKGROUND 
       [0003]    Since the advent of desktop publishing in the mid-1980s, it has become increasingly easy to use commonly-available software to create and print letters, cards, documents, and other printed matter. Moreover, at the present time, a computer user may have scores or even hundreds of high-quality fonts installed on his or her computer, with thousands of additional free and commercial fonts available via the Internet. As a result, many people have become accustomed to receiving printed materials that are not hand-written. Indeed, hand-written notes and cards may signal to a recipient a sense of importance and particular care because the sender personally took the effort to hand-craft the message. 
         [0004]    There are numerous fonts that are intended to mimic generic handwriting to a certain extent. There are even services that will create a font to mimic a particular person&#39;s handwriting. However, existing personalized-handwriting fonts may appear mechanical and/or unnatural because individual glyphs may always be printed with identical geometry, whereas in an actual hand-written document, each individual character may have its own subtly unique geometry. Moreover, existing personalized-handwriting fonts and personalized-handwriting-font-creation services may have difficulty isolating individual glyph within a sample of cursive handwriting or other handwriting in which adjacent letters may be connected to one another. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0005]      FIG. 1  illustrates an exemplary variable glyph processing system in accordance with one embodiment. 
           [0006]      FIG. 2  illustrates several components of an exemplary variable glyph processing device in accordance with one embodiment. 
           [0007]      FIG. 3  illustrates a glyph representations identification routine in accordance with one embodiment. 
           [0008]      FIG. 4  illustrates a glyph representation identification subroutine in accordance with one embodiment. 
           [0009]      FIG. 5  illustrates an exemplary bitmap of the word “Lapdog” in accordance with one embodiment. 
           [0010]      FIG. 6  illustrates a down-sampled and filtered bitmap in accordance with one embodiment. 
           [0011]      FIG. 7  illustrates a pixel pattern in accordance with one embodiment. 
           [0012]      FIG. 8  illustrates rectangular connections in a pixel pattern in accordance with one embodiment. 
           [0013]      FIGS. 9-10  illustrate a skeletonized bitmap in accordance with one embodiment. 
           [0014]      FIG. 11  illustrates connected graphs derived from a skeletonized bitmap in accordance with one embodiment. 
           [0015]      FIG. 12  illustrates segmented components within a bitmap in accordance with one embodiment. 
           [0016]      FIG. 13  shows illustrative exemplars for the six glyphs making up the word “Lapdog” in accordance with one embodiment. 
           [0017]      FIGS. 14-16  illustrate simulations with the illustrative pattern recognition routine for the word “Lapdog” in accordance with one embodiment. 
           [0018]      FIG. 17  illustrates a variable glyph transformation subroutine in accordance with one embodiment. 
           [0019]      FIG. 18  illustrates a glyph geometric-property distribution-function subroutine in accordance with one embodiment. 
           [0020]      FIG. 19  illustrates an exemplary transformation applied to a base glyph representation in accordance with one embodiment. 
       
    
    
     DESCRIPTION 
       [0021]    The detailed description that follows is represented largely in terms of processes and symbolic representations of operations by conventional computer components, including a processor, memory storage devices for the processor, connected display devices and input devices. Furthermore, these processes and operations may utilize conventional computer components in a heterogeneous distributed computing environment, including remote file Servers, computer Servers and memory storage devices. Each of these conventional distributed computing components is accessible by the processor via a communication network. 
         [0022]    Reference is now made in detail to the description of the embodiments as illustrated in the drawings. While embodiments are described in connection with the drawings and related descriptions, there is no intent to limit the scope to the embodiments disclosed herein. On the contrary, the intent is to cover all alternatives, modifications and equivalents. In alternate embodiments, additional devices, or combinations of illustrated devices, may be added to, or combined, without limiting the scope to the embodiments disclosed herein. 
         [0023]      FIG. 1  illustrates an exemplary variable glyph processing system  100  in which a client device  115  and a variable glyph processing server  200  are connected to a network  150 . In some embodiments, some or all of variable glyph processing server  200  and client device  115 , may be incorporated into a single logical or physical device. As used herein, the term “glyph” refers to a symbol, letter, number, or other graphic or typographical representation. 
         [0024]    In various embodiments, network  150  may include the Internet, a local area network (“LAN”), a wide area network (“WAN”), and/or other data network. In some embodiments, there may be multiple client devices  115  and/or multiple variable glyph processing servers  200 . 
         [0025]      FIG. 2  illustrates several components of an exemplary variable glyph processing device  200 . In some embodiments, variable glyph processing device  200  may include many more components than those shown in  FIG. 2 . However, it is not necessary that all of these generally conventional components be shown in order to disclose an illustrative embodiment. As shown in  FIG. 2 , the variable glyph processing device  200  includes an optional communication interface  205  for connecting to a network. 
         [0026]    The variable glyph processing server  200  also includes a processing unit  210 , a memory  250 , and an optional display  240 , all interconnected along with the communication interface  205  via a bus  220 . Memory  250  generally comprises a random access memory (“RAM”), a read only memory (“ROM”), and a permanent mass storage device, such as a disk drive. The memory  250  stores program code for a variable glyph rendering routine  300 , a glyph representations identification subroutine  400 , a variable glyph transformation routine  1700 , and store  125  of glyph representations. In addition, the memory  250  also stores an operating system  255 . These software components may be loaded from a computer readable storage medium  295  into memory  250  of the variable glyph processing server  200  using a drive mechanism (not shown) associated with a computer readable storage medium, such as a floppy disc, tape, DVD/CD-ROM drive, memory card, or the like. In some embodiments, software components may also be loaded via the communication interface  205 , rather than via a computer readable storage medium  295 . 
         [0027]    Although an exemplary variable glyph processing server  200  has been described that generally conforms to conventional general purpose computing devices, an variable glyph processing server  200  may be any of a great number of devices capable of communicating with the network  150  and/or client device  115 , for example, a personal computer, a game console, a set-top box, a handheld computer, a cell phone, a cloud computing service, or any other device that is capable of processing variable glyph data. 
         [0028]      FIG. 3  illustrates a glyph-representations identification routine  300  in accordance with one embodiment. In block  305 , routine  300  obtains one or more images of handwritten text. In one embodiment, the one or more images of handwritten text may be scanned or otherwise acquired by client device  115  and conveyed to variable glyph processing device  200  via network  150  or other means. In one embodiment, 1200 dpi may be a suitable scanning resolution, but other resolutions may be used in other embodiments. Other embodiments may employ alternate means of acquiring an image of handwritten text. For example, an image may be acquired from a picture taken by a camera or by a camera component of a multipurpose device (e.g., a mobile phone with integrated camera). 
         [0029]    Beginning in block  310 , routine  300  processes each obtained image of handwritten text in turn. In subroutine block  400 , routine  300  calls glyph representation identification subroutine  400  (see  FIG. 4 , discussed below) to identify glyph representations within the current image of handwritten text. In block  320 , routine  300  cycles back to block  310  to process the next image of handwritten text (if any). This and other processes are described herein as iterative processes for clarity of explanation, but in other embodiments, processes may be performed in parallel and/or according to control structures other than iteration. 
         [0030]    In block  325 , routine  300  obtains one or more glyphs to vary. For example, routine may obtain a passage of text and/or a string of characters to render in variable glyphs. Beginning in block  330 , routine  300  processes each glyph. In subroutine block  1700 , routine  300  calls variable glyph transformation routine  1700  (see  FIG. 17 , discussed below) to obtain a varied representation for the current glyph. 
         [0031]    In block  340 , routine  300  renders the varied glyph representation. For example, in one embodiment, routine  300  may output the varied glyph representation to a screen, printer, or other graphical output device. In other embodiments, routine  300  may output the varied glyph representation to a file for further processing. In block  345 , routine  300  cycles back to block  330  to process the next glyph (if any). Routine  300  ends at block  399 . 
         [0032]      FIG. 4  illustrates a glyph-representation identification subroutine  400  in accordance with one embodiment. In some embodiments, subroutine  400  may be related to the concept of “word segmentation.” In the context of automated handwriting synthesis, “word segmentation” refers to the process of taking an image of a handwritten copy of a known word or text and matching segments of the image with the corresponding glyphs that make up the word. In various embodiments, word segmentation may allow for ligature identification in bigram formation and/or for the derivation of statistical information, e.g., from the isolation of individual glyphs, about variables that may characterize handwriting, such as the variability in glyph size, orientation, and spacing. 
         [0033]    In block  405 , subroutine  400  obtains an image of a handwritten copy of a known word or text, typically scanned or imaged at a suitable resolution (e.g., 1200 dpi, although other embodiments may use higher or lower resolutions). In one embodiment, the image may be passed in from a calling routine (e.g., see discussion of block  305  and  315  of  FIG. 3 , above). In block  410 , subroutine  400  preprocesses the image. In one embodiment, the image of the word or text, is converted to a bitmap, or a corresponding set of “on” and “off” pixels. 
         [0034]    In some embodiments, the bitmap may be further preprocessed according to one or more image processing routines (not shown). For example, in one embodiment, additional image processing routines include down sampling and filtering. Other embodiments may use more or fewer image processing routines. If used, the down sampling image processing algorithm may improve the efficiency of subroutine  400  while retaining at least some characteristics of the original bitmap. In one embodiment, down sampled bitmaps result in a 10-fold reduction in number of pixels. Other embodiments may down sample to a greater or lesser degree. In one embodiment, the bitmap is also filtered to remove artifacts that may have been introduced by the scanning or image capture process. 
         [0035]      FIG. 5  illustrates an exemplary bitmap  500  of the word “Lapdog,” which illustrates artifacts including scatter  505 A-C, which are small isolated sets of “on” pixels, and hole  510 , which is a small isolated interior set of “off” pixels.  FIG. 6  illustrates bitmap  600 , which is a down-sampled and filtered version of bitmap  500 . 
         [0036]    Referring again to  FIG. 4 , in block  415 , unconnected or disjoint components of the processed bitmap are identified. In one embodiment, unconnected or disjoint components of the processed bitmap are identified by finding the connected components of the grid graph corresponding to the processed bitmap. As illustrated in  FIG. 6 , three disjoint components  605 ,  610 , and  615  may be identified in bitmap  600 . 
         [0037]    Beginning in block  420 , subroutine  400  processes each identified disjoint component. In block  425 , subroutine  400  skeletonizes the current disjoint component. In one embodiment, a skeletonization process may comprise a thinning routine specifically tailored for word segmentation. In other embodiments, thinning routines that are not specifically tailored may be employed. In an illustrative embodiment, the skeletonization process comprises two stages. In stage one of the illustrative skeletonization process, the approximate rise and fall in ligatures between adjacent glyphs in a component are located, for example, by scanning the image from top to bottom and determining the median pixel in each horizontal line of pixels. For example, as illustrated in  FIG. 7 , each solid-black box outside dashed rectangles  705  and  710  in pixel pattern  700  represents the location of the median pixel for the corresponding line segment. Dashed rectangles  705  and  710  each indicate a change in topology. For dashed rectangle  705 , two distinct line segments have joined, in which case the illustrative thinning routine extends the solid-black pixels from the two pixel segments downward one pixel. For dashed rectangle  710 , a single segment is about to split into two line segments, in which case the solid-black pixels or medians of the two lower line segments are extended upward one pixel. 
         [0038]    In the second stage of the illustrative skeletonization process, the skeletonization process finds rectangular connections between the solid-black pixels determined in stage one. In the illustrative routine, a rectangular connection is a nondiagonal edge between two adjacent nodes or pixels. In finding rectangular connections, the illustrative skeletonization process generates a rectangular or grid graph, in which the solid-black pixels become part of the node set of the graph and are connected by edges.  FIG. 8  illustrates rectangular connections  805  derived from the solid-black pixels identified in pixel pattern  700 . 
         [0039]    This grid graph is also referred to as the thin skeleton. As illustrated in  FIG. 9 , the thin skeleton  935  captures topological information inherent in the original component image. For example, the illustrative thinning process captures the short tails  905 ,  910  rising and falling in the ligatures  920 ,  930  between the “a” and “p” and the “d” and “o.” 
         [0040]    Referring again to  FIG. 4 , in block  430 , the thin skeleton is used to generate a connected path or thick black path through the component image, the connected path traversing the ligatures connecting the glyphs from left to right.  FIG. 9  also illustrates a connected path  915  through the component image, the connected path  915  traversing ligatures  920 ,  925 ,  930  connecting the glyphs from left to right. 
         [0041]    Referring again to  FIG. 4 , in block  435 , some or all nodes of the thin skeleton that are not merely connecting nodes (i.e. nodes with three or more paths) are classified according to type and location. In the illustrative embodiment, such nodes are classified as either Real or Pseudo. In one embodiment, Real nodes generally indicate the presence of a connection between distinct sections of the image. Turning points are frequently found near Pseudo nodes so that Pseudo nodes may indicate the presence of a ligature. In other embodiments, other classifications may be used.  FIG. 10  illustrates Real nodes  1010 A-F on connected path  915  and Pseudo nodes  1005 A-J on connected path  915  and thin skeleton  935 . 
         [0042]    Referring again to  FIG. 4 , in block  440 , an edge detection routine detects edge sets of “on” pixels in the image component and generates connected graphs of some or all such boundaries in the component image. In block  445 , the connected graphs are classified according to their relative locations. For example, as illustrated in  FIG. 11 , connected graphs  1105 - 1135  are classified as upper main coast  1105 , lower main coast  1115 , or as individual interior coasts  1110 ,  1120 ,  1125 ,  1130 ,  1135 . In other embodiments, other classifications may be used, or connected graphs may not be classified. 
         [0043]    In some embodiments, Real nodes and Pseudo nodes may also be classified according to location. For example, a real or pseudo node may lie on the outer coast of the image or on an inland coast or be an interior point. 
         [0044]    Referring again to  FIG. 4 , in block  450 , the component image is traversed along the corresponding connected path, and information gleaned from the node classifications (if any) and edge sets is used to judiciously section the component image into non-overlapping segments. As a component is traversed in the illustrative embodiment, trial cuts are made at or near some or all Real or Pseudo nodes along the connected path. Exemplary criteria for accepting a trial cut include a sufficiently large horizontal distance traveled from the last accepted cut, and whether the cut extends from the upper to lower main coast. In other embodiments, other criteria may be employed. 
         [0045]    As illustrated in  FIG. 12 , components  605  and  615  (i.e. “L” and “g”) have been sectioned by the illustrative segmentation process into single segments, while component  610  has been partitioned into seven segments  1220 - 1250 . In  FIG. 12 , segments  1220 - 1250  are depicted in alternating light and dark shades merely for the purposes of visualization. 
         [0046]    Referring again to  FIG. 4 , beginning in block  455 , patterns are recognized within sets of adjacent segments. For each character in the letter, word, or text represented by the current disjoint component, in block  460 , some or all sets of adjacent segments may be determined and compared with an image of a corresponding exemplar, which may be provided by the individual, and the best match determined. ( FIG. 13  shows illustrative exemplars for the six glyphs  1305 - 1330  making up the word “Lapdog.”) 
         [0047]    In one embodiment, the pattern recognition routine is based on a generalized minimum distance, which can be considered to be a variation on the notion of Hausdorff metric between two compact subsets of a metric space. In other embodiments, other pattern recognition routines may be used. The illustrative pattern recognition routine is now briefly summarized. 
         [0048]    Let eS denote the zero set of a bit map of an image taken to be the exemplar and let tS denote the bit map of a test or comparison image. 
         [0049]    For each zero set, an ordered set may be found from a complementary normalized zero set close to the normalized zero set in the following sense. Let the normalized zero set be that of the exemplar eS. Find a point tS Min (u i ) from tSN closest to u i  for every point u i  in eSN. Repeating this process for the normalized test zero set tSN, the following sets are obtained: 
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         [0050]    Continuing to describe the illustrative pattern recognition routine, two affine mappings may be generated, T eS  and T tS , one for the exemplar and the other for the test zero set. Together, the two affine mappings minimize a particular sum of squares objective function H, described below. The illustrative affine mapping T has the general form 
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         [0051]    The illustrative affine mapping T applies shear, scaling, rotation and translation to a point (x,y) and requires seven parameters to be completely specified. In other embodiments, more, fewer, and/or different parameters may specify an alternate affine mapping T. 
         [0052]    In one embodiment, the objective function to be minimized is as follows: 
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                                     y 
                                     
                                       S 
                                       t 
                                     
                                   
                                   , 
                                   
                                     θ 
                                     t 
                                   
                                   , 
                                   
                                     o 
                                     
                                       x 
                                       t 
                                     
                                   
                                   , 
                                   
                                     o 
                                     
                                       y 
                                       t 
                                     
                                   
                                   , 
                                   
                                     s 
                                     
                                       x 
                                       t 
                                     
                                   
                                   , 
                                   
                                     s 
                                     
                                       y 
                                       t 
                                     
                                   
                                 
                                 ) 
                               
                             
                           
                           } 
                         
                         . 
                         
                           
 
                         
                          
                         
                             
                         
                          
                         where 
                       
                        
                       
                           
                       
                        
                       α 
                     
                     = 
                     
                       0.005 
                        
                       
                           
                       
                        
                       and 
                     
                   
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   9 
                 
               
             
             
               
                 
                   
                     F 
                      
                     
                       ( 
                       
                         
                           x 
                           
                             S 
                             e 
                           
                         
                         , 
                         
                           y 
                           
                             S 
                             e 
                           
                         
                         , 
                         
                           θ 
                           e 
                         
                         , 
                         
                           o 
                           
                             x 
                             e 
                           
                         
                         , 
                         
                           o 
                           
                             y 
                             e 
                           
                         
                         , 
                         
                           
                             s 
                             
                               
                                 x 
                                 e 
                               
                               , 
                             
                           
                            
                           
                             s 
                             
                               y 
                               e 
                             
                           
                         
                       
                       ) 
                     
                   
                   = 
                   
                     
                       1 
                       
                         card 
                          
                         
                           ( 
                           eSN 
                           ) 
                         
                       
                     
                      
                     
                       
                         ∑ 
                         
                           
                             u 
                             i 
                           
                           = 
                           
                             
                               ( 
                               
                                 
                                   
                                     
                                       x 
                                       i 
                                     
                                   
                                 
                                 
                                   
                                     
                                       y 
                                       i 
                                     
                                   
                                 
                               
                               ) 
                             
                             ∈ 
                             eSN 
                           
                         
                       
                        
                       
                         
                           
                              
                             
                               
                                 u 
                                 i 
                               
                               - 
                               
                                 
                                   T 
                                   e 
                                 
                                  
                                 
                                   
                                     tS 
                                     Min 
                                   
                                    
                                   
                                     ( 
                                     
                                       u 
                                       i 
                                     
                                     ) 
                                   
                                 
                               
                             
                              
                           
                           2 
                           2 
                         
                         . 
                       
                     
                   
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   10 
                 
               
             
             
               
                 
                   
                     G 
                      
                     
                       ( 
                       
                         
                           x 
                           
                             S 
                             t 
                           
                         
                         , 
                         
                           y 
                           
                             S 
                             t 
                           
                         
                         , 
                         
                           θ 
                           t 
                         
                         , 
                         
                           o 
                           
                             x 
                             t 
                           
                         
                         , 
                         
                           o 
                           
                             y 
                             t 
                           
                         
                         , 
                         
                           s 
                           
                             x 
                             t 
                           
                         
                         , 
                         
                           s 
                           
                             y 
                             t 
                           
                         
                       
                       ) 
                     
                   
                   = 
                   
                     
                       1 
                       
                         card 
                          
                         
                           ( 
                           tSN 
                           ) 
                         
                       
                     
                      
                     
                       
                         ∑ 
                         
                           
                             u 
                             i 
                           
                           = 
                           
                             
                               ( 
                               
                                 
                                   
                                     
                                       x 
                                       i 
                                     
                                   
                                 
                                 
                                   
                                     
                                       y 
                                       i 
                                     
                                   
                                 
                               
                               ) 
                             
                             ∈ 
                             tSN 
                           
                         
                       
                        
                       
                         
                           
                              
                             
                               
                                 u 
                                 i 
                               
                               - 
                               
                                 
                                   T 
                                   t 
                                 
                                  
                                 
                                   
                                     eS 
                                     Min 
                                   
                                    
                                   
                                     ( 
                                     
                                       u 
                                       i 
                                     
                                     ) 
                                   
                                 
                               
                             
                              
                           
                           2 
                           2 
                         
                         . 
                       
                     
                   
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   11. 
                 
               
             
           
         
       
     
         [0000]    In particular, 
         [0000]    
       
         
           
             
               
                 
                   
                     F 
                      
                     
                       ( 
                       
                         
                           x 
                           
                             S 
                             e 
                           
                         
                         , 
                         
                           y 
                           
                             S 
                             e 
                           
                         
                         , 
                         
                           θ 
                           e 
                         
                         , 
                         
                           o 
                           
                             x 
                             e 
                           
                         
                         , 
                         
                           o 
                           
                             y 
                             e 
                           
                         
                         , 
                         
                           
                             s 
                             
                               
                                 x 
                                 e 
                               
                               , 
                             
                           
                            
                           
                             s 
                             
                               y 
                               e 
                             
                           
                         
                       
                       ) 
                     
                   
                   = 
                   
                     
                       
                         1 
                         
                           card 
                            
                           
                             ( 
                             eSN 
                             ) 
                           
                         
                       
                        
                       
                         
                           ∑ 
                           
                             
                               u 
                               i 
                             
                             = 
                             
                               
                                 ( 
                                 
                                   
                                     
                                       
                                         x 
                                         i 
                                       
                                     
                                   
                                   
                                     
                                       
                                         y 
                                         i 
                                       
                                     
                                   
                                 
                                 ) 
                               
                               ∈ 
                               eSN 
                             
                           
                         
                          
                         
                           
                             ( 
                             
                               
                                 x 
                                 i 
                               
                               - 
                               
                                 
                                   ( 
                                   
                                     
                                       T 
                                       
                                         x 
                                         , 
                                         1 
                                       
                                       e 
                                     
                                      
                                     
                                         
                                     
                                      
                                     
                                       T 
                                       
                                         y 
                                         , 
                                         1 
                                       
                                       e 
                                     
                                   
                                   ) 
                                 
                                  
                                 
                                   
                                     tS 
                                     Min 
                                   
                                    
                                   
                                     ( 
                                     
                                       u 
                                       i 
                                     
                                     ) 
                                   
                                 
                               
                             
                             ) 
                           
                           2 
                         
                       
                     
                     + 
                     
                       
                         
                           ( 
                           
                             
                               y 
                               i 
                             
                             - 
                             
                               
                                 ( 
                                 
                                   
                                     T 
                                     
                                       x 
                                       , 
                                       2 
                                     
                                     e 
                                   
                                    
                                   
                                       
                                   
                                    
                                   
                                     T 
                                     
                                       y 
                                       , 
                                       2 
                                     
                                     e 
                                   
                                 
                                 ) 
                               
                                
                               
                                 
                                   tS 
                                   Min 
                                 
                                  
                                 
                                   ( 
                                   
                                     u 
                                     i 
                                   
                                   ) 
                                 
                               
                             
                           
                           ) 
                         
                         2 
                       
                       . 
                     
                   
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   12 
                 
               
             
             
               
                 
                   
                     F 
                      
                     
                       ( 
                       
                         
                           x 
                           
                             S 
                             e 
                           
                         
                         , 
                         
                           y 
                           
                             S 
                             e 
                           
                         
                         , 
                         
                           θ 
                           e 
                         
                         , 
                         
                           o 
                           
                             x 
                             e 
                           
                         
                         , 
                         
                           o 
                           
                             y 
                             e 
                           
                         
                         , 
                         
                           
                             s 
                             
                               
                                 x 
                                 e 
                               
                               , 
                             
                           
                            
                           
                             s 
                             
                               y 
                               e 
                             
                           
                         
                       
                       ) 
                     
                   
                   = 
                   
                     
                       1 
                       
                         card 
                          
                         
                           ( 
                           eSN 
                           ) 
                         
                       
                     
                      
                     
                       
                         ∑ 
                         
                           
                             u 
                             i 
                           
                           = 
                           
                             
                               ( 
                               
                                 
                                   
                                     
                                       x 
                                       i 
                                     
                                   
                                 
                                 
                                   
                                     
                                       y 
                                       i 
                                     
                                   
                                 
                               
                               ) 
                             
                             ∈ 
                             eSN 
                           
                         
                       
                        
                       
                           
                         
                           
                             { 
                             
                               
                                 
                                   
                                     
                                       ( 
                                       
                                         
                                           
                                             
                                               
                                                 x 
                                                 i 
                                               
                                               - 
                                               
                                                 o 
                                                 
                                                   x 
                                                   e 
                                                 
                                               
                                               - 
                                               
                                                 
                                                   x 
                                                   
                                                     S 
                                                     e 
                                                   
                                                 
                                                  
                                                 
                                                   p 
                                                   i 
                                                 
                                                  
                                                 
                                                   cos 
                                                    
                                                   
                                                     ( 
                                                     
                                                       θ 
                                                       e 
                                                     
                                                     ) 
                                                   
                                                 
                                               
                                               - 
                                             
                                           
                                         
                                         
                                           
                                             
                                               
                                                 
                                                   y 
                                                   
                                                     S 
                                                     e 
                                                   
                                                 
                                                  
                                                 
                                                   q 
                                                   i 
                                                 
                                                  
                                                 
                                                   s 
                                                   
                                                     x 
                                                     e 
                                                   
                                                 
                                                  
                                                 
                                                   cos 
                                                    
                                                   
                                                     ( 
                                                     
                                                       θ 
                                                       e 
                                                     
                                                     ) 
                                                   
                                                 
                                               
                                               - 
                                               
                                                 
                                                   x 
                                                   
                                                     S 
                                                     e 
                                                   
                                                 
                                                  
                                                 
                                                   p 
                                                   i 
                                                 
                                                  
                                                 
                                                   s 
                                                   
                                                     x 
                                                     e 
                                                   
                                                 
                                                  
                                                 
                                                   s 
                                                   
                                                     y 
                                                     e 
                                                   
                                                 
                                                  
                                                 
                                                   cos 
                                                    
                                                   
                                                     ( 
                                                     
                                                       θ 
                                                       e 
                                                     
                                                     ) 
                                                   
                                                 
                                               
                                               + 
                                             
                                           
                                         
                                         
                                           
                                             
                                               
                                                 
                                                   x 
                                                   
                                                     s 
                                                     e 
                                                   
                                                 
                                                  
                                                 
                                                   q 
                                                   i 
                                                 
                                                  
                                                 
                                                   sin 
                                                    
                                                   
                                                     ( 
                                                     
                                                       θ 
                                                       e 
                                                     
                                                     ) 
                                                   
                                                 
                                               
                                               - 
                                               
                                                 
                                                   y 
                                                   
                                                     S 
                                                     e 
                                                   
                                                 
                                                  
                                                 
                                                   p 
                                                   i 
                                                 
                                                  
                                                 
                                                   s 
                                                   
                                                     x 
                                                     e 
                                                   
                                                 
                                                  
                                                 
                                                   sin 
                                                    
                                                   
                                                     ( 
                                                     
                                                       θ 
                                                       e 
                                                     
                                                     ) 
                                                   
                                                 
                                               
                                               + 
                                             
                                           
                                         
                                         
                                           
                                             
                                               
                                                 x 
                                                 
                                                   S 
                                                   e 
                                                 
                                               
                                                
                                               
                                                 q 
                                                 i 
                                               
                                                
                                               
                                                 s 
                                                 
                                                   s 
                                                   e 
                                                 
                                               
                                                
                                               
                                                 s 
                                                 
                                                   y 
                                                   e 
                                                 
                                               
                                                
                                               
                                                 sin 
                                                  
                                                 
                                                   ( 
                                                   
                                                     θ 
                                                     e 
                                                   
                                                   ) 
                                                 
                                               
                                             
                                           
                                         
                                       
                                       ) 
                                     
                                     + 
                                   
                                 
                               
                               
                                 
                                   
                                     ( 
                                     
                                       
                                         
                                           
                                             
                                               y 
                                               i 
                                             
                                             - 
                                             
                                               o 
                                               
                                                 y 
                                                 e 
                                               
                                             
                                             - 
                                             
                                               
                                                 y 
                                                 
                                                   S 
                                                   e 
                                                 
                                               
                                                
                                               
                                                 q 
                                                 i 
                                               
                                                
                                               
                                                 s 
                                                 
                                                   x 
                                                   e 
                                                 
                                               
                                                
                                               
                                                 cos 
                                                  
                                                 
                                                   ( 
                                                   
                                                     θ 
                                                     e 
                                                   
                                                   ) 
                                                 
                                               
                                             
                                             - 
                                           
                                         
                                       
                                       
                                         
                                           
                                             
                                               
                                                 x 
                                                 
                                                   S 
                                                   e 
                                                 
                                               
                                                
                                               
                                                 p 
                                                 i 
                                               
                                                
                                               
                                                 s 
                                                 
                                                   y 
                                                   e 
                                                 
                                               
                                                
                                               
                                                 cos 
                                                  
                                                 
                                                   ( 
                                                   
                                                     θ 
                                                     e 
                                                   
                                                   ) 
                                                 
                                               
                                             
                                             - 
                                             
                                               
                                                 y 
                                                 
                                                   S 
                                                   e 
                                                 
                                               
                                                
                                               
                                                 p 
                                                 i 
                                               
                                                
                                               
                                                 sin 
                                                  
                                                 
                                                   ( 
                                                   
                                                     θ 
                                                     e 
                                                   
                                                   ) 
                                                 
                                               
                                             
                                             + 
                                           
                                         
                                       
                                       
                                         
                                           
                                             
                                               x 
                                               
                                                 S 
                                                 e 
                                               
                                             
                                              
                                             
                                               q 
                                               i 
                                             
                                              
                                             
                                               s 
                                               
                                                 y 
                                                 e 
                                               
                                             
                                              
                                             
                                               sin 
                                                
                                               
                                                 ( 
                                                 
                                                   θ 
                                                   e 
                                                 
                                                 ) 
                                               
                                             
                                           
                                         
                                       
                                     
                                     ) 
                                   
                                 
                               
                             
                             } 
                           
                           . 
                           
                             
 
                           
                            
                           
                               
                           
                            
                           and 
                         
                       
                     
                   
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   13 
                 
               
             
             
               
                 
                   
                       
                   
                    
                   
                     
                       ( 
                       
                         
                           
                             
                               p 
                               i 
                             
                           
                         
                         
                           
                             
                               q 
                               i 
                             
                           
                         
                       
                       ) 
                     
                     = 
                     
                       
                         
                           tS 
                           Min 
                         
                          
                         
                           ( 
                           
                             u 
                             i 
                           
                           ) 
                         
                       
                       . 
                       
                         
 
                       
                        
                       
                           
                       
                        
                       where 
                     
                   
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   14 
                 
               
             
             
               
                 
                   
                       
                   
                    
                   
                     
                       u 
                       i 
                     
                     = 
                     
                       
                         ( 
                         
                           
                             
                               
                                 x 
                                 i 
                               
                             
                           
                           
                             
                               
                                 y 
                                 i 
                               
                             
                           
                         
                         ) 
                       
                       ∈ 
                       
                         eSN 
                         . 
                       
                     
                   
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   15 
                 
               
             
           
         
       
     
         [0053]    Continuing to describe the illustrative pattern recognition routine, the objective function H is minimized. The optimal parameters x s     {circumflex over (t)}   , y s     {circumflex over (t)}   , θ {circumflex over (t)} , o x     {circumflex over (t)}   , o y     {circumflex over (t)}   , s x     {circumflex over (t)}   , s y     {circumflex over (t)}    and x s     ê   , y s     ê   , θ e     ê   , o x     ê   , o y     ê   , s x     ê   , s y     ê    are then employed in the affine mapping to transform, respectively, eSN and tSN to 
         [0000]        eŜN=T ( x   s     {circumflex over (t)}     , y   s     {circumflex over (t)}     , θ   {circumflex over (t)}   , o   x     {circumflex over (t)}     , o   y     {circumflex over (t)}     , s   x     {circumflex over (t)}     , s   y     {circumflex over (t)}   ) eSN    Equation 16.
 
         [0000]        tŜN=T ( x   s     ê     , y   s     ê     , θ   ê   , o   x     ê     , o   y     ê     , s   x     ê     , s   y     ê   ) tSN.    Equation 17.
 
         [0054]    In one embodiment, the illustrative pattern recognition routine is then iterated until an increase in the objective function minimum is detected. In one embodiment, three iterations may be utilized, but more or fewer iterations may be used in other embodiments. 
         [0055]      FIG. 14  illustrates one possible simulation with the illustrative pattern recognition routine for the word “Lapdog.” From the fact that there are nine non-overlapping segments for the three-disjoint-component six-glyph word, there are only 20 ordered sets out of a total of 56 to examine. The first ordered set considered is Ordered Set 4={{1}, {2}, {3}, {4}, {5,6,7,8}, {9}} which indicates that glyph 1 (“L”) is represented by segment 1, glyph 2 (“a”) by segment 2, glyph 3 (“p”) by segment 3, glyph 4 (“d”) by segment 4, glyph 5 (“o”) by segments 5,6,7,8 and glyph 6 (“g”) by segment 9. The set of dissimilarity measures for this ordered set is determined by the routine to be {0.703292, 1.0673, 339.052, 1.19132, 3.7673, 0.497561}. According to the simulation illustrated in  FIG. 14 , all choices are reasonably good except for the representation of glyph “p” by segment 3, which is two orders of magnitude larger than the rest. 
         [0056]      FIG. 15  depicts several ordered sets with small dissimilarity measures for the handwritten word “Lapdog” as determined by the illustrative pattern recognition routine.  FIG. 16  depicts an ordered set with large dissimilarity measures for the handwritten word “Lapdog” as determined by the illustrative pattern recognition routine. 
         [0057]    Referring again to  FIG. 4 , once a set of one or more adjacent non-overlapping segments have been determined for the current character, the set is stored as a representation of the corresponding glyph. In one embodiment, the set is stored as a member of an ensemble of representations of the corresponding glyph. 
         [0058]    In block  470 , subroutine  400  cycles back to block  455  to process the next character. In block  475 , subroutine  400  cycles back to block  420  to process the next disjoint component. Subroutine  400  returns to the caller in block  499 . 
         [0059]      FIG. 17  illustrates a variable glyph transformation subroutine  1700  in accordance with one embodiment. As the term is used herein, a glyph representation includes, but is not limited to a centerline, i.e. a set of points describing the middle or interior of a glyph; a glyph skin, or set of points along the glyph surface; and a set of points comprising the glyph (i.e. the glyph ‘bitmap’). As the term is used herein, a base representation of a glyph refers to a representation of the glyph in a two dimensional space. It includes but is not limited to a centerline, i.e. a set of points describing the middle or interior of a glyph; a glyph skin, or set of points along the glyph surface; and a set of point comprising the glyph (i.e. the glyph “bitmap”). The base glyph representation may or may not have originated from a bitmap of a scan of handwritten text. In one embodiment, a linear transform of the form 
         [0000]      x i →x i A+b   Equation 18.
 
         [0000]    is applied to {x i }, the set of two dimensional coordinates comprising the representation, yielding a transformed representation of the glyph. Quantities A and b are determined from statistical measurements of geometrical properties from an ensemble of representations of the glyph or similar glyphs. (See  FIGS. 18-18 , discussed below.) These representations may or may not have originated from a bitmap of a scan of handwritten text. The representations in an ensemble may or may not include the base glyph representation. 
         [0060]    In subroutine block  1800  (see  FIG. 18 , discussed immediately below), subroutine  1700  obtains geometric-property distribution functions corresponding to a glyph to be transformed. 
         [0061]      FIG. 18  illustrates a glyph geometric-property distribution-function subroutine  1800  in accordance with one embodiment. In block  1805 , subroutine  1800  obtains an ensemble of glyph representations. For example, in one embodiment, an ensemble of glyph representations may be obtained via one or more invocations of subroutine  400  (see  FIG. 4 , discussed above). In some embodiments, an ensemble of glyph representations may be obtained from a store of glyph representations  225 . 
         [0062]    Beginning in block  1810 , one or more glyph geometric properties are processed. In one embodiment, glyph geometry may be specifically defined. In one embodiment, measures that describe glyph geometry include, a glyph position above a baseline, a glyph size, and a glyph orientation. 
         [0063]    Beginning in block  1815 , each member of the ensemble of glyph representations is processed. In block  1820 , subroutine  1800  calculates a measure of the current glyph geometric property for the current member of the ensemble of glyph representations. For example, in one embodiment, one of the following measures may be taken: a measure of the glyph representation&#39;s position above a baseline, a measure of the spatial orientation of the glyph representation, and one or more measures of a size of the glyph representation.  FIG. 19  illustrates an exemplary set of glyph geometric properties for a base glyph representation  1900 . 
       Glyph Position Above a Baseline 
       [0064]    The base glyph representation  1900 , as well as any representations in an ensemble of glyph representations, may originate from scans of handwritten text that has been written above a baseline  1925 . The position of a glyph representation (e.g.  1900 ) above the baseline  1905 , denoted h, may be defined as 
         [0000]        h =Σ( y   i   −b )/ N    Equation 19.
 
         [0000]    where {y i } are the vertical coordinates of all points in the representation, N is the number of points in the representation, and b is the vertical position of the baseline  1925 . Alternative definitions include a root-mean-squared distance above the baseline, i.e. 
         [0000]        h =√{square root over (Σ( y   i   −b ) 2   /N )}.   Equation 20.
 
       Glyph Size and Orientation 
       [0065]    For any two dimensional object, including a glyph representation (e.g.  1900 ), principal moments of inertia, p 1  and p 2  ( 1915  and  1910 , respectively), are calculated by diagonalizing the moment of inertia tensor given by 
         [0000]    
       
         
           
             
               
                 
                   I 
                   = 
                   
                     
                       [ 
                       
                         
                           
                             
                               I 
                               xx 
                             
                           
                           
                             
                               I 
                               xy 
                             
                           
                         
                         
                           
                             
                               I 
                               yx 
                             
                           
                           
                             
                               I 
                               yy 
                             
                           
                         
                       
                       ] 
                     
                     . 
                     
                       
 
                     
                      
                     where 
                   
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   21 
                 
               
             
             
               
                 
                   
                     
                       I 
                       xx 
                     
                     = 
                     
                       ∑ 
                       
                         y 
                         i 
                         2 
                       
                     
                   
                   , 
                   
                     
                       I 
                       yy 
                     
                     = 
                     
                       
                         ∑ 
                         
                           
                             x 
                             i 
                             2 
                           
                           . 
                           
                             
 
                           
                            
                           
                             I 
                             yx 
                           
                         
                       
                       = 
                       
                         
                           I 
                           xy 
                         
                         = 
                         
                           ∑ 
                           
                             
                               x 
                               i 
                             
                              
                             
                               y 
                               i 
                             
                           
                         
                       
                     
                   
                   , 
                 
               
               
                 
                   Equation 
                    
                   
                       
                   
                    
                   22. 
                 
               
             
           
         
       
     
         [0066]    If the original image of the glyph is drawn on a baseline, then the angle  1920  between the baseline and the first principal axis, denoted α, gives a spatial orientation of the representation. The norms of the principal moments, |p 1 | and |p 2 |, give a measurement of the size of the representation in the directions of the principal moments of inertia  1915 ,  1910 . 
         [0067]    Referring again to  FIG. 18 , in block  1825 , subroutine  1800  at least transiently stores the calculated measure of the current glyph geometric property (e.g., one of h, α, and |p 1 | and |p 2 |). In block  1830 , subroutine  1800  cycles back to block  1815  to process the next ensemble member (if any). 
         [0068]    In block  1835 , subroutine  1800  determines a statistical distribution function for the current glyph geometric property. In one embodiment, having determined measures of the current glyph geometric property for each member of the ensemble of glyph representations, subroutine  1800  determines statistical metrics for the ensemble of determined measures, including the mean and the variance. In one embodiment, these statistical metrics may then be used to define distribution functions, such as the Gaussian distributions, that model the distribution of the measures in the ensemble. 
         [0069]    In block  1840 , subroutine  1800  stores the determined statistical distribution function for the current glyph geometric property. In block  1845 , subroutine  1800  cycles back to block  1810  to process the next glyph geometric property (if any). Subroutine  1800  ends in block  1899 . 
         [0070]    Referring again to  FIG. 17 , in block  1710 , subroutine  1700  obtains a base representation for the glyph to be transformed. In one embodiment, the base representation may originate from a scan or scans of handwritten text. In some embodiments, the base representation may be obtained from a store of glyph representations  225 . 
         [0071]    In block  1715 , subroutine  1700  obtains target values for the glyph geometric properties. In one embodiment, target values of for the glyph geometric properties (e.g., h′, α′, |p 1 |′ and |p 2 |′) may be determined by sampling from the distribution functions of these measures defined for the glyph representation ensembles. 
         [0072]    In block  1720 , subroutine  1700  transforms the base glyph representation into a target representation. In one embodiment, a unique transformation in the form of Equation 18 (above) maps the base glyph representation to a target representation that has the desired values for the corresponding geometrical properties. For example,  FIG. 19  illustrates an exemplary transformation applied to base glyph representation  1900  yielding a target representation  1900 ′ of the glyph having target values h′, α′, |p 1 |′ and |p 2 |′ for the corresponding glyph geometric properties. 
         [0073]    Referring again to  FIG. 17 , subroutine  1700  returns to the caller in block  1799 . 
         [0074]    Although specific embodiments have been illustrated and described herein, it will be appreciated by those of ordinary skill in the art that a whole variety of alternate and/or equivalent implementations may be substituted for the specific embodiments shown and described without departing from the scope of the present invention. This application is intended to cover any adaptations or variations of the embodiments discussed herein.