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Introduction
                         Method
         Testing and Evaluation
         Results and Discussions
                       Summary




Implementation and Evaluation of Document
 Retrieval for the PC Notes Taker (PCNT)
             Handwriting Device

                     Nasir Mahmood

        Otto - von - Guericke University, Magdeburg


                    November 1, 2007



                Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction
                                     Method
                     Testing and Evaluation
                     Results and Discussions
                                   Summary


Outline



      Introduction
      Method
      Testing and Evaluation
      Results and Discussions
      Summary




                            Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Handwriting
                                     Method    Digital Handwriting
                     Testing and Evaluation    Handwriting Acquisition
                     Results and Discussions   Document Retrieval
                                   Summary     Aim of the Work


Handwriting

      Handwriting is used for
            literary writing
            correspondence
            advertisement
            ...
      its electronic articulation are
            typewriter
            computer
      hasn’t lost importance due to claims of
        1   authenticity
        2   (inter-)mediality
        3   coporeality


                            Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Handwriting
                                    Method    Digital Handwriting
                    Testing and Evaluation    Handwriting Acquisition
                    Results and Discussions   Document Retrieval
                                  Summary     Aim of the Work


Digital Handwriting



      Digital representation of the information of a user ’s
      handwriting

      A way to convert written words from the ink on paper to
      digital format

      Acquisition Approaches
        1   Offline handwriting acuquisition
        2   Online handwriting acquisition




                           Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Handwriting
                                  Method    Digital Handwriting
                  Testing and Evaluation    Handwriting Acquisition
                  Results and Discussions   Document Retrieval
                                Summary     Aim of the Work


Offline Handwriting Acquisition

      Visual representation of a text
      No dynamic information
      A scanned image of handwriting is
      digitally read in
      Applications
          Optical Character Recognition (OCR)
          Intelligent Character Recognition (ICR)

      Disadvantages
          noise from scanning the text
          lines or patterns
          extra marks due to dust or scratches

                         Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Handwriting
                                     Method    Digital Handwriting
                     Testing and Evaluation    Handwriting Acquisition
                     Results and Discussions   Document Retrieval
                                   Summary     Aim of the Work


Online Handwriting Acquisition

       The way a text is written is important
       Digital ink signal:
             a sequence of 2D points over time
             information of strokes & trajectories

       Devices to capture digital ink
         1   digital pen on a patterned paper
         2   paper-based capture device
         3   pen-sensitive surface (touch screen)

       Advantages
             No optical noise, easier data processing
             Broad range of applications

                            Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Handwriting
                                     Method    Digital Handwriting
                     Testing and Evaluation    Handwriting Acquisition
                     Results and Discussions   Document Retrieval
                                   Summary     Aim of the Work


Document Retrieval

   Given a set D of documents and a query word q, find a list D of
   documents where q occurs at least once
          D = {d1 , d2 , d3 , ..., dn }
          D = {d1 , d2 , d3 , ..., dn }
   query q and documents D are handwritten
   Document Retrieval Methods
    1 Textual recognition

             most intuitive, simple string search on textual features
             fails in most searches, not suitable for hand-drawn images
     2   Direct handwriting matching
             works for all kinds of scripts and images
             our method lives under this catergory

                            Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Handwriting
                                   Method    Digital Handwriting
                   Testing and Evaluation    Handwriting Acquisition
                   Results and Discussions   Document Retrieval
                                 Summary     Aim of the Work


Aim of the Work


      Part A:
       1   Introduction of sub-features used for document retrieval
       2   Comparision of existing and newly introduced features

      Part B:
       1   Implementation of document retrieval system for PC Notes
           Taker (PCNT) device
       2   Evaluation of our method against PCNT and its comparsion
           with those already tested




                          Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Document Retrieval Algorithms
                                     Method    Approximate String Search
                     Testing and Evaluation    Handwriting Features
                     Results and Discussions   Square Freeman Grid Codes
                                   Summary     Triangular Freeman Grid Codes


Document Retrieval Algorithms

   Ideal Retrieval Algorithm
    1   low complexity
    2   works with simple features
    3   faster and accurate

   Existing Approaches
        Image feature indexing (Srihari et al.)
        Pattern recognition & maching learning (Schomaker et al.)
        Graph matching approach (Fonseca et al.)
        String matching (Sun et al.)


                            Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Document Retrieval Algorithms
                                      Method    Approximate String Search
                      Testing and Evaluation    Handwriting Features
                      Results and Discussions   Square Freeman Grid Codes
                                    Summary     Triangular Freeman Grid Codes


String Algorithms - Approximate String Search

      How close two strings (query & its instance in document) are.
      Edit distance, most common similarity measure
      Approximate String Search - Local Alignment
            fuzzy search of short string (q) within a longer one (d)
            a matrix D of dimension (m + 1)x(n + 1)
            m and n are length of q and d
            for a match D(m, j) < τ , τ is a threshold

                 > 0                                         if i = 0,
                 8                                                               9
                                                                                 >
                 > D(i − 1, 0) + 1
                 >
                 <                                           if i > 0 and j = 0, >
                                                                                 >
                                                                                 =
                       8                            9
       D(i, j) =       < D(i, j − 1) + 1            =
                 > min    D(i − 1, j) + 1                    else,
                 >                                                                      >
                                                                                        >
                 >
                 :                                                                      >
                                                                                        ;
                          D(i − 1, j − 1) + δ(i, j)
                       :                            ;
                                                             ff
                                      0 if q[i] = d[j],
                         δ(i, j) =
                                      1 else,

                             Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Document Retrieval Algorithms
                                    Method    Approximate String Search
                    Testing and Evaluation    Handwriting Features
                    Results and Discussions   Square Freeman Grid Codes
                                  Summary     Triangular Freeman Grid Codes


Handwriting Features


      Feature data represent ink traces of a writing process
      Approximate string search works with string features
      String features: xt , yt position of pen tip over time t
      Freeman grid codes - string features
        1   discretization of data with a grid
        2   assignment of codes to discretized data

      Square Freeman grid codes
      Triangular Freeman grid codes


                           Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Document Retrieval Algorithms
                                   Method    Approximate String Search
                   Testing and Evaluation    Handwriting Features
                   Results and Discussions   Square Freeman Grid Codes
                                 Summary     Triangular Freeman Grid Codes


Square Freeman Grid Codes


    Two sets of evenly spaced lines perpendicular
    to each other - square grid

    Handwritten input is superimposed on the grid
    Sample points xt , yt are mapped to nodes
    Each sample point gets one of 8 symbols
    9th symbol to encode a gap

    Encoded ink shape is sequence of symbols
    rather than sample points xt , yt


                          Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Document Retrieval Algorithms
                               Method    Approximate String Search
               Testing and Evaluation    Handwriting Features
               Results and Discussions   Square Freeman Grid Codes
                             Summary     Triangular Freeman Grid Codes


Square Freeman Grid Codes




                      Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Document Retrieval Algorithms
                                     Method    Approximate String Search
                     Testing and Evaluation    Handwriting Features
                     Results and Discussions   Square Freeman Grid Codes
                                   Summary     Triangular Freeman Grid Codes


Triangular Freeman Grid Codes



    Three sets of lines at 60-degree angle to each
    other - triangular grid

    Quantization and assignment of codes for
    feature extraction is similar to square grid
    type except
      1   Triangular grid to sumperimpose
          handwriting onto
      2   Six node symbols to map sample points



                            Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Document Retrieval Algorithms
                                     Method    Approximate String Search
                     Testing and Evaluation    Handwriting Features
                     Results and Discussions   Square Freeman Grid Codes
                                   Summary     Triangular Freeman Grid Codes


Triangular Freeman Grid Codes




                     1
                         √
    h = a sin60o =   2       3a



                             Nasir Mahmood     Document Retrieval for PC Notes Taker
Introduction   Document Retrieval Algorithms
                               Method    Approximate String Search
               Testing and Evaluation    Handwriting Features
               Results and Discussions   Square Freeman Grid Codes
                             Summary     Triangular Freeman Grid Codes


Triangular Freeman Grid Codes




                      Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Document Retrieval Algorithms
                                Method    Approximate String Search
                Testing and Evaluation    Handwriting Features
                Results and Discussions   Square Freeman Grid Codes
                              Summary     Triangular Freeman Grid Codes


Freeman Codes




                       Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction
                                     Method    PC Notes Taker Device (PCNT)
                     Testing and Evaluation    Data Collection
                     Results and Discussions   Performance Measures
                                   Summary


Pegasus PC Notes Taker Device (PCNT)


   PCNT captures handwriting online                           PCNT device




   Its package comes with
     1   a cordless electronic pen
     2   a detachable base with USB cable

   For applications, its SDK is available to
     1   to capture data from device
     2   to process it accordingly

   Coverage area: A4 size paper
   Resolution: 1200 DPI

                            Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction
                                    Method    PC Notes Taker Device (PCNT)
                    Testing and Evaluation    Data Collection
                    Results and Discussions   Performance Measures
                                  Summary


Data Collection

    No suitable testset database available
    Built our own database
        in English and Urdu scripts
        documents written with PCNT
        documents read in with SDK

    Database
        80 documents by 8 persons
        5 documents per person in each script
        documents contents - repetitive
        words/phrases
        29 queries manually selected & tagged
        804 true matches selected & tagged

                           Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction
                                  Method    PC Notes Taker Device (PCNT)
                  Testing and Evaluation    Data Collection
                  Results and Discussions   Performance Measures
                                Summary


Data Collection




                         Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction
                                   Method    PC Notes Taker Device (PCNT)
                   Testing and Evaluation    Data Collection
                   Results and Discussions   Performance Measures
                                 Summary


Performance Measures

   Search operation results in
       matches,
       mismatches and
       missed instances

   Retrieval measures:
                             matches
        Precision =    matches+mismatches

                               matches
        Recall rate =      matches+missings

                           2×precision×recall
        F1 measure =        precision+recall


                          Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Freeman Grid Codes
                                  Method    Square Freeman Grid Codes
                  Testing and Evaluation    Triangular Freeman Grid Codes
                  Results and Discussions   Square Vs. Triangular Grid Codes
                                Summary     Performance with PC Notes Taker Device (PCNT)


Freeman Grid Codes



      Square Freeman codes

      Triangular Freeman codes

      Square vs. Triangulare Freeman codes

      Freeman codes: PCNT vs. ioPen




                         Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Freeman Grid Codes
                               Method    Square Freeman Grid Codes
               Testing and Evaluation    Triangular Freeman Grid Codes
               Results and Discussions   Square Vs. Triangular Grid Codes
                             Summary     Performance with PC Notes Taker Device (PCNT)


Square Freeman Grid Codes




                      Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Freeman Grid Codes
                               Method    Square Freeman Grid Codes
               Testing and Evaluation    Triangular Freeman Grid Codes
               Results and Discussions   Square Vs. Triangular Grid Codes
                             Summary     Performance with PC Notes Taker Device (PCNT)


Triangular Freeman Grid Codes




                      Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction   Freeman Grid Codes
                                Method    Square Freeman Grid Codes
                Testing and Evaluation    Triangular Freeman Grid Codes
                Results and Discussions   Square Vs. Triangular Grid Codes
                              Summary     Performance with PC Notes Taker Device (PCNT)


Square Vs. Triangular Grid Codes




                       Nasir Mahmood      Document Retrieval for PC Notes Taker
Introduction    Freeman Grid Codes
                                   Method     Square Freeman Grid Codes
                   Testing and Evaluation     Triangular Freeman Grid Codes
                   Results and Discussions    Square Vs. Triangular Grid Codes
                                 Summary      Performance with PC Notes Taker Device (PCNT)


Performance with PC Notes Taker Device (PCNT)


                 PCNT Device                               ioPen Device
    GS     P        R    F1             T          P           R    F1   T
     6   76.51    78.78 0.78           8458      81.50       81.50 0.81 1555
    8    78.68    76.97 0.78           4644      82.30       78.90 0.80 1607
    10   78.98    74.80 0.77           2810      78.30       78.80 0.78 572
    12   79.47    73.10 0.76           2007      77.10       73.90 0.75 451
    16   81.49    67.74 0.74           1326      73.80       71.60 0.72 284

   GS = Grid size, P = Precision (%)
   R = Recall rate (%), T = Time (milliseconds)


                          Nasir Mahmood       Document Retrieval for PC Notes Taker
Introduction
                                  Method
                  Testing and Evaluation    Summary
                  Results and Discussions
                                Summary


Summary

     Retrieval System
          Approximate string search - retrieval algorithm
          It works with all kinds of scripts/figures

     Handwriting Features
          Freeman to convert handwriting signals to code string
          Introduced triangular Freeman features: 6 equidistant
          directions rather than 8 directions of square Freeman features
          Little performance difference with both types of features

     PC Notes Taker
          To build database, documents written in Urdu & English
          benchmark: using triangluar and square Freeman features
          No performace difference from earlier tests with ioPen

                         Nasir Mahmood      Document Retrieval for PC Notes Taker

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Implementation and Evaluation of Document Retrieval System

  • 1. Introduction Method Testing and Evaluation Results and Discussions Summary Implementation and Evaluation of Document Retrieval for the PC Notes Taker (PCNT) Handwriting Device Nasir Mahmood Otto - von - Guericke University, Magdeburg November 1, 2007 Nasir Mahmood Document Retrieval for PC Notes Taker
  • 2. Introduction Method Testing and Evaluation Results and Discussions Summary Outline Introduction Method Testing and Evaluation Results and Discussions Summary Nasir Mahmood Document Retrieval for PC Notes Taker
  • 3. Introduction Handwriting Method Digital Handwriting Testing and Evaluation Handwriting Acquisition Results and Discussions Document Retrieval Summary Aim of the Work Handwriting Handwriting is used for literary writing correspondence advertisement ... its electronic articulation are typewriter computer hasn’t lost importance due to claims of 1 authenticity 2 (inter-)mediality 3 coporeality Nasir Mahmood Document Retrieval for PC Notes Taker
  • 4. Introduction Handwriting Method Digital Handwriting Testing and Evaluation Handwriting Acquisition Results and Discussions Document Retrieval Summary Aim of the Work Digital Handwriting Digital representation of the information of a user ’s handwriting A way to convert written words from the ink on paper to digital format Acquisition Approaches 1 Offline handwriting acuquisition 2 Online handwriting acquisition Nasir Mahmood Document Retrieval for PC Notes Taker
  • 5. Introduction Handwriting Method Digital Handwriting Testing and Evaluation Handwriting Acquisition Results and Discussions Document Retrieval Summary Aim of the Work Offline Handwriting Acquisition Visual representation of a text No dynamic information A scanned image of handwriting is digitally read in Applications Optical Character Recognition (OCR) Intelligent Character Recognition (ICR) Disadvantages noise from scanning the text lines or patterns extra marks due to dust or scratches Nasir Mahmood Document Retrieval for PC Notes Taker
  • 6. Introduction Handwriting Method Digital Handwriting Testing and Evaluation Handwriting Acquisition Results and Discussions Document Retrieval Summary Aim of the Work Online Handwriting Acquisition The way a text is written is important Digital ink signal: a sequence of 2D points over time information of strokes & trajectories Devices to capture digital ink 1 digital pen on a patterned paper 2 paper-based capture device 3 pen-sensitive surface (touch screen) Advantages No optical noise, easier data processing Broad range of applications Nasir Mahmood Document Retrieval for PC Notes Taker
  • 7. Introduction Handwriting Method Digital Handwriting Testing and Evaluation Handwriting Acquisition Results and Discussions Document Retrieval Summary Aim of the Work Document Retrieval Given a set D of documents and a query word q, find a list D of documents where q occurs at least once D = {d1 , d2 , d3 , ..., dn } D = {d1 , d2 , d3 , ..., dn } query q and documents D are handwritten Document Retrieval Methods 1 Textual recognition most intuitive, simple string search on textual features fails in most searches, not suitable for hand-drawn images 2 Direct handwriting matching works for all kinds of scripts and images our method lives under this catergory Nasir Mahmood Document Retrieval for PC Notes Taker
  • 8. Introduction Handwriting Method Digital Handwriting Testing and Evaluation Handwriting Acquisition Results and Discussions Document Retrieval Summary Aim of the Work Aim of the Work Part A: 1 Introduction of sub-features used for document retrieval 2 Comparision of existing and newly introduced features Part B: 1 Implementation of document retrieval system for PC Notes Taker (PCNT) device 2 Evaluation of our method against PCNT and its comparsion with those already tested Nasir Mahmood Document Retrieval for PC Notes Taker
  • 9. Introduction Document Retrieval Algorithms Method Approximate String Search Testing and Evaluation Handwriting Features Results and Discussions Square Freeman Grid Codes Summary Triangular Freeman Grid Codes Document Retrieval Algorithms Ideal Retrieval Algorithm 1 low complexity 2 works with simple features 3 faster and accurate Existing Approaches Image feature indexing (Srihari et al.) Pattern recognition & maching learning (Schomaker et al.) Graph matching approach (Fonseca et al.) String matching (Sun et al.) Nasir Mahmood Document Retrieval for PC Notes Taker
  • 10. Introduction Document Retrieval Algorithms Method Approximate String Search Testing and Evaluation Handwriting Features Results and Discussions Square Freeman Grid Codes Summary Triangular Freeman Grid Codes String Algorithms - Approximate String Search How close two strings (query & its instance in document) are. Edit distance, most common similarity measure Approximate String Search - Local Alignment fuzzy search of short string (q) within a longer one (d) a matrix D of dimension (m + 1)x(n + 1) m and n are length of q and d for a match D(m, j) < τ , τ is a threshold > 0 if i = 0, 8 9 > > D(i − 1, 0) + 1 > < if i > 0 and j = 0, > > = 8 9 D(i, j) = < D(i, j − 1) + 1 = > min D(i − 1, j) + 1 else, > > > > : > ; D(i − 1, j − 1) + δ(i, j) : ;  ff 0 if q[i] = d[j], δ(i, j) = 1 else, Nasir Mahmood Document Retrieval for PC Notes Taker
  • 11. Introduction Document Retrieval Algorithms Method Approximate String Search Testing and Evaluation Handwriting Features Results and Discussions Square Freeman Grid Codes Summary Triangular Freeman Grid Codes Handwriting Features Feature data represent ink traces of a writing process Approximate string search works with string features String features: xt , yt position of pen tip over time t Freeman grid codes - string features 1 discretization of data with a grid 2 assignment of codes to discretized data Square Freeman grid codes Triangular Freeman grid codes Nasir Mahmood Document Retrieval for PC Notes Taker
  • 12. Introduction Document Retrieval Algorithms Method Approximate String Search Testing and Evaluation Handwriting Features Results and Discussions Square Freeman Grid Codes Summary Triangular Freeman Grid Codes Square Freeman Grid Codes Two sets of evenly spaced lines perpendicular to each other - square grid Handwritten input is superimposed on the grid Sample points xt , yt are mapped to nodes Each sample point gets one of 8 symbols 9th symbol to encode a gap Encoded ink shape is sequence of symbols rather than sample points xt , yt Nasir Mahmood Document Retrieval for PC Notes Taker
  • 13. Introduction Document Retrieval Algorithms Method Approximate String Search Testing and Evaluation Handwriting Features Results and Discussions Square Freeman Grid Codes Summary Triangular Freeman Grid Codes Square Freeman Grid Codes Nasir Mahmood Document Retrieval for PC Notes Taker
  • 14. Introduction Document Retrieval Algorithms Method Approximate String Search Testing and Evaluation Handwriting Features Results and Discussions Square Freeman Grid Codes Summary Triangular Freeman Grid Codes Triangular Freeman Grid Codes Three sets of lines at 60-degree angle to each other - triangular grid Quantization and assignment of codes for feature extraction is similar to square grid type except 1 Triangular grid to sumperimpose handwriting onto 2 Six node symbols to map sample points Nasir Mahmood Document Retrieval for PC Notes Taker
  • 15. Introduction Document Retrieval Algorithms Method Approximate String Search Testing and Evaluation Handwriting Features Results and Discussions Square Freeman Grid Codes Summary Triangular Freeman Grid Codes Triangular Freeman Grid Codes 1 √ h = a sin60o = 2 3a Nasir Mahmood Document Retrieval for PC Notes Taker
  • 16. Introduction Document Retrieval Algorithms Method Approximate String Search Testing and Evaluation Handwriting Features Results and Discussions Square Freeman Grid Codes Summary Triangular Freeman Grid Codes Triangular Freeman Grid Codes Nasir Mahmood Document Retrieval for PC Notes Taker
  • 17. Introduction Document Retrieval Algorithms Method Approximate String Search Testing and Evaluation Handwriting Features Results and Discussions Square Freeman Grid Codes Summary Triangular Freeman Grid Codes Freeman Codes Nasir Mahmood Document Retrieval for PC Notes Taker
  • 18. Introduction Method PC Notes Taker Device (PCNT) Testing and Evaluation Data Collection Results and Discussions Performance Measures Summary Pegasus PC Notes Taker Device (PCNT) PCNT captures handwriting online PCNT device Its package comes with 1 a cordless electronic pen 2 a detachable base with USB cable For applications, its SDK is available to 1 to capture data from device 2 to process it accordingly Coverage area: A4 size paper Resolution: 1200 DPI Nasir Mahmood Document Retrieval for PC Notes Taker
  • 19. Introduction Method PC Notes Taker Device (PCNT) Testing and Evaluation Data Collection Results and Discussions Performance Measures Summary Data Collection No suitable testset database available Built our own database in English and Urdu scripts documents written with PCNT documents read in with SDK Database 80 documents by 8 persons 5 documents per person in each script documents contents - repetitive words/phrases 29 queries manually selected & tagged 804 true matches selected & tagged Nasir Mahmood Document Retrieval for PC Notes Taker
  • 20. Introduction Method PC Notes Taker Device (PCNT) Testing and Evaluation Data Collection Results and Discussions Performance Measures Summary Data Collection Nasir Mahmood Document Retrieval for PC Notes Taker
  • 21. Introduction Method PC Notes Taker Device (PCNT) Testing and Evaluation Data Collection Results and Discussions Performance Measures Summary Performance Measures Search operation results in matches, mismatches and missed instances Retrieval measures: matches Precision = matches+mismatches matches Recall rate = matches+missings 2×precision×recall F1 measure = precision+recall Nasir Mahmood Document Retrieval for PC Notes Taker
  • 22. Introduction Freeman Grid Codes Method Square Freeman Grid Codes Testing and Evaluation Triangular Freeman Grid Codes Results and Discussions Square Vs. Triangular Grid Codes Summary Performance with PC Notes Taker Device (PCNT) Freeman Grid Codes Square Freeman codes Triangular Freeman codes Square vs. Triangulare Freeman codes Freeman codes: PCNT vs. ioPen Nasir Mahmood Document Retrieval for PC Notes Taker
  • 23. Introduction Freeman Grid Codes Method Square Freeman Grid Codes Testing and Evaluation Triangular Freeman Grid Codes Results and Discussions Square Vs. Triangular Grid Codes Summary Performance with PC Notes Taker Device (PCNT) Square Freeman Grid Codes Nasir Mahmood Document Retrieval for PC Notes Taker
  • 24. Introduction Freeman Grid Codes Method Square Freeman Grid Codes Testing and Evaluation Triangular Freeman Grid Codes Results and Discussions Square Vs. Triangular Grid Codes Summary Performance with PC Notes Taker Device (PCNT) Triangular Freeman Grid Codes Nasir Mahmood Document Retrieval for PC Notes Taker
  • 25. Introduction Freeman Grid Codes Method Square Freeman Grid Codes Testing and Evaluation Triangular Freeman Grid Codes Results and Discussions Square Vs. Triangular Grid Codes Summary Performance with PC Notes Taker Device (PCNT) Square Vs. Triangular Grid Codes Nasir Mahmood Document Retrieval for PC Notes Taker
  • 26. Introduction Freeman Grid Codes Method Square Freeman Grid Codes Testing and Evaluation Triangular Freeman Grid Codes Results and Discussions Square Vs. Triangular Grid Codes Summary Performance with PC Notes Taker Device (PCNT) Performance with PC Notes Taker Device (PCNT) PCNT Device ioPen Device GS P R F1 T P R F1 T 6 76.51 78.78 0.78 8458 81.50 81.50 0.81 1555 8 78.68 76.97 0.78 4644 82.30 78.90 0.80 1607 10 78.98 74.80 0.77 2810 78.30 78.80 0.78 572 12 79.47 73.10 0.76 2007 77.10 73.90 0.75 451 16 81.49 67.74 0.74 1326 73.80 71.60 0.72 284 GS = Grid size, P = Precision (%) R = Recall rate (%), T = Time (milliseconds) Nasir Mahmood Document Retrieval for PC Notes Taker
  • 27. Introduction Method Testing and Evaluation Summary Results and Discussions Summary Summary Retrieval System Approximate string search - retrieval algorithm It works with all kinds of scripts/figures Handwriting Features Freeman to convert handwriting signals to code string Introduced triangular Freeman features: 6 equidistant directions rather than 8 directions of square Freeman features Little performance difference with both types of features PC Notes Taker To build database, documents written in Urdu & English benchmark: using triangluar and square Freeman features No performace difference from earlier tests with ioPen Nasir Mahmood Document Retrieval for PC Notes Taker