ENCLOSURE 6, PAGE 1

EXAMPLE OF FORM TO BE RETURNED FOR EACH TEST RESULT SUBMITTED FOR SCORING

OBLIGATORY RESPONSES:

  SYSTEM NAME:

  PARTICIPANT NAME:

VOLUNTARY RESPONSES:

1. CHARACTER SEGMENTATION (PLEASE CHECK APPROPRIATE BOXES.):
    DONE BEFORE CHARACTER RECOGNITION ................. [ ]
    DONE ITERATIVELY WITH CHARACTER RECOGNITION ....... [ ]
     CHECKING DICTIONARY AS PART OF ITERATIVE PROCESS . [ ]
    DONE SIMULTANEOUSLY WITH CHARACTER RECOGNITION .... [ ]
    BLOB COLORING ..................................... [ ]
    SPATIAL HISTOGRAMS ................................ [ ]
    LOCAL MINIMA AND MAXIMA ........................... [ ]
    INTENTIONAL OVER SEGMENTATION ..................... [ ]
    STROKE RECONSTRUCTION ............................. [ ]
    VARIABLE SCALE NETWORKS ........................... [ ]
    CENTRAL OBJECT .................................... [ ]
    TIME DOMAIN NEURAL NETWORK ........................ [ ]
    OTHER: ............................................ [ ]______________ 

2. CHARACTER RECOGNITION

2.1 PREPROCESSING (PLEASE CHECK APPROPRIATE BOXES.):
     CONVERSION TO GREY SCALE ......................... [ ]
     HEIGHT/WIDTH NORMALIZATION WHILE PRESERVING SHAPE  [ ]
     SEPARATE NORMALIZATIONS FOR HEIGHT AND WIDTH .....	[ ]
     SLANT NORMALIZATION .............................. [ ]
     ROTATION ......................................... [ ]
     LOCAL SUPPORT (GABOR, WAVELET, ETC.) ............. [ ]
     FOURIER OR SIMILAR TRANSFORM ..................... [ ]
     OTHER: ........................................... [ ]______________ 

2.2 SEPARATE FEATURE EXTRACTION AND CLASSIFICATION: 	[ ] YES
     IF YES GO TO QUESTION 3, ELSE GO TO QUESTION 5.

2.3 FEATURE EXTRACTION (PLEASE CHECK APPROPRIATE BOXES.):
    *ADAPTIVE LEARNING ................................ [ ]
     +SUPERVISED ...................................... [ ]
       TIME DOMAIN NEURAL NETWORK ..................... [ ]
       RECEPTOR FIELDS ................................ [ ]
       OTHER SUPERVISED: .............................. [ ]_______________ 
     +SELF-ORGANIZED .................................. [ ]
       KOHONEN MAPS ................................... [ ]
       NEO-COGNITRON .................................. [ ]
       OTHER SELF-ORGANIZED: .......................... [ ]_______________ 
     +OTHER ADAPTIVE: ................................. [ ]_______________ 
    *RULE-BASED ....................................... [ ]
     +LINEARIZING TRANSFORMS .......................... [ ]
       LINE FIT ....................................... [ ]
       POLYNOMIAL ..................................... [ ]
       OTHER LINEARIZING TRANSFORM: ................... [ ]_______________ 
     +CONVOLUTION/CORRELATION ......................... [ ]
      -TRANSFORMS ..................................... [ ]
        HAND CODED .................................... [ ]
        GABOR ......................................... [ ]
        OTHER TRANSFORMS: ............................. [ ]_______________ 
      -TEMPLATES ...................................... [ ]
      -OTHER CONVOLUTION/ETC: ......................... [ ]_______________ 
     +MODEL ........................................... [ ]
ENCLOSURE 6, PAGE 2

       STROKES ........................................ [ ]
       SHAPES ......................................... [ ]
       HOLES .......................................... [ ]
       CAVITIES ....................................... [ ]
       MORPHOLOGICAL .................................. [ ]
       OTHER MODEL: ................................... [ ]_______________ 
     +STATISTICAL ..................................... [ ]
       PRINCIPAL COMPONENT ANALYSIS (K-L TRANSFORM) ... [ ]
       HISTOGRAM ...................................... [ ]
       OTHER STATISTICAL: ............................. [ ]_______________ 
     +OTHER RULE-BASED: ............................... [ ]_______________ 

2.3 CLASSIFICATION (PLEASE CHECK APPROPRIATE BOXES)
    *ADAPTIVE LEARNING ................................ [ ]
     +SUPERVISED ...................................... [ ]
       MULTI-LAYER PERCEPTRON ......................... [ ]
       LEARNED VECTOR QUANTIZATION .................... [ ]
       REDUCED COULOMB ENERGY ......................... [ ] 
       AFFINE TRANSFORMATION .......................... [ ] 
       OTHER SUPERVISED: .............................. [ ]_______________ 
     +SELF-ORGANIZED .................................. [ ] 
       CASCADED NEURAL NETWORK ........................ [ ] 
       LOOK-UP TABLE .................................. [ ] 
       PROBABILITY NEURAL NETWORK ..................... [ ] 
       OTHER SELF-ORGANIZED: .......................... [ ]_______________ 
     +OTHER ADAPTIVE: ................................. [ ]_______________ 
    *RULE-BASED ....................................... [ ]
     +GEOMETRIC ....................................... [ ] 
       NEAREST NEIGHBOR ............................... [ ] 
       K-NEAREST NEIGHBOR ............................. [ ] 
       OTHER GEOMETRIC: ............................... [ ]_______________ 
     +STATISTICAL ..................................... [ ] 
       PROBABILITY .................................... [ ] 
       QDF ............................................ [ ]  
       POLYNOMIAL ..................................... [ ] 
       OTHER STATISTICAL: ............................. [ ]_______________ 
     +OTHER RULE-BASED: ............................... [ ]_______________ 

2.5 HYBRID FEATURE EXTRACTION AND CLASSIFICATION: PLEASE GIVE A DESCRIPTIVE
    NAME FOR YOUR APPROACH USING TERMS FROM QUESTIONS 3 AND 4 WHERE
    APPROPRIATE.
    _______________________________________________________________________ 

3. DICTIONARY-BASED CORRECTION (PLEASE CHECK APPROPRIATE BOXES.):
   *NOT DONE (REQUEST NIST CORRECTION) ................ [ ]
   *NOT DONE (REQUEST NO FURTHER CORRECTION) .......... [ ]
   *DONE AFTER CHARACTER RECOGNITION .................. [ ]
    +FIRST (OR ONLY) PASS THROUGH A DICTIONARY ........ [ ]
      WORDS IN DICTIONARY CODED AS LETTERS ............ [ ]
      WORDS IN DICTIONARY CODED AS OTHER .............. [ ]________________
      SEARCH ENTIRE DICTIONARY ........................ [ ] 
      SEARCH SUBSET OF DICTIONARY ..................... [ ] 
      HASHED OR INDEXED SEARCH OF DICTIONARY .......... [ ] 
      EXACT MATCH REQUIRED ............................ [ ]
      STATISTICAL DISTANCE MEASURE MINIMIZED .......... [ ]
      OTHER DISTANCE MEASURE MINIMIZED ................ [ ]________________
    +SECOND PASS THROUGH A DICTIONARY ................. [ ]
      WORDS IN DICTIONARY CODED AS LETTERS ............ [ ]
      WORDS IN DICTIONARY CODED AS OTHER .............. [ ]________________
      SEARCH ENTIRE DICTIONARY ........................ [ ] 
      SEARCH SUBSET OF DICTIONARY ..................... [ ] 
      HASHED OR INDEXED SEARCH OF DICTIONARY .......... [ ] 
      EXACT MATCH REQUIRED ............................ [ ]
      STATISTICAL DISTANCE MEASURE MINIMIZED .......... [ ]

ENCLOSURE 6, PAGE 3

      OTHER DISTANCE MEASURE MINIMIZED ................ [ ]________________
    +MORE THAN TWO PASSES THROUGH DICTIONARIES ........ [ ]
   *DONE ITERATIVELY WITH CHARACTER RECOGNITION ....... [ ]
     WORDS IN DICTIONARY CODED AS LETTERS ............. [ ]
     WORDS IN DICTIONARY CODED AS OTHER ............... [ ]________________
     SEARCH ENTIRE DICTIONARY ......................... [ ] 
     SEARCH SUBSET OF DICTIONARY ...................... [ ] 
     HASHED OR INDEXED SEARCH OF DICTIONARY ........... [ ] 
     EXACT MATCH REQUIRED ............................. [ ]
     STATISTICAL DISTANCE MEASURE MINIMIZED ........... [ ]
     OTHER DISTANCE MEASURE MINIMIZED ................. [ ]________________

4. OTHER CONTEXT BASED CORRECTION ..................... [ ]
    LETTERS BY SAME WRITER ............................ [ ]
    WORDS OR PHRASES BY SAME WRITER ................... [ ]
    OTHER: ............................................ [ ]________________

5. PLEASE ATTACH A LIST OF REFERENCES TO YOUR PERTINENT PUBLICATIONS.

6. PLEASE ATTACH A LIST OF REFERENCES TO YOUR GENERAL TECHNIQUES, IF NOT
   ALREADY DESCRIBED IN AN ATTACHED LIST OF REFERENCES.

7. IF THE ABOVE QUESTIONS DO NOT CAPTURE THE ESSENCE OF YOUR SYSTEM,
   PLEASE PROVIDE AN ATTACHMENT THAT DOES. 

8. IF OTHER THAN THE DIGITS, THE UPPER CASE LETTERS, AND THE LOWER CASE
   LETTERS, PLEASE STATE THE FULL CHARACTER SET THAT YOUR SYSTEM
   RECOGNIZES.
