Loop Investigation for Cursive Handwriting Processing and Recognition By Tal Steinherz Advanced...

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Transcript of Loop Investigation for Cursive Handwriting Processing and Recognition By Tal Steinherz Advanced...

  • Loop Investigation for Cursive Handwriting Processing and RecognitionBy Tal Steinherz

    Advanced Seminar (Spring 05)

  • OutlineBackground on cursive handwriting

    Introduction to loopsPattern recognition and machine learning conflictsFeature extraction solutionsDemonstrations and experimental results

  • Cursive Handwriting (J. C. Simon)Displacing a pen from left to right in an oscillating movement, with loops, descendants (legs), and ascendants (poles).

  • Cursive vs. CharacterCursive continuous concatenated set of strokes. produced by a human being in a free style.Character a single standalone symbol. produced by a machine subjected to numerous alternative fonts.

  • Online vs. OfflineOnline captured by pen-like devices. the input format is a two-dimensional signal of pixel locations as a function of time (x(t),y(t)).Offline captured by scanning devices. the input format is a two-dimensional image of gray-scale colors as a function of location I(m*n). strokes have significant width.

  • Online vs. Offline (demo)

  • A Loop (T. Steinherz)A set of neighboring foreground pixels surrounding a hole, i.e., a connected blocked group of background pixels in the words image, where all foreground pixels are within stroke width distance from the hole.

  • Ascending (Descending) Loops

  • Axial (of the middle zone) Loops

  • The importance of loops Shared by many letters (especially a,d,e,g,o,p,q)Byproduct of the continuous nature of cursive handwriting (like with b,f,h,j,k,l,s,t,y,z)Elementary and prominent featuresCarry additional information given by a set of descriptive parameters

  • The motivation to investigate loopsCharacter recognition supports discrimination between letters.Writer modelingIdentificationExaminationcontributes to applications in forensic science and graphology.

  • The output of loop investigationIncomplete (open) loop identificationHidden (collapsed) loop tracking - locating blobs that correspond to online loopsMulti (encapsulated) loops understanding - distinguishing natural from artificial loopsTemporal information recovery - retracing the original path of a pen

  • The Engineering Approach(J. C. Simon & T. Pavlidis)Requires understanding the structure of the objects to be recognized and apply the appropriate combination of (pattern recognition) techniques.

  • Feature extraction dilemmasOffline cursive word signal representationLoop identificationSignal to noise ratioFeature vector translation

    The difficulties consist in the feature extraction and preprocessing rather than the machine learning \ recognition engine phase.

  • Offline cursive word signal representationWe use the external upper and lower contours in conjunction with the internal contour of all visible loops.

  • Loop identificationGiven a set of singular points, identification is provided by correlation between pieces of the same contour (around anchor points), of the opposite contours and\or in association with subsets of internal contours.

  • Signal to noise ratioIn order to improve the signals parametric quantifiability and reduce noisy artifacts, the contour is transformed to a polygon.

  • Hidden loop tracking -the mutual distance principle

  • Hidden loop tracking -the mutual distance principle (cont.)

  • Hidden loop tracking -the mutual distance principle (cont.)

  • Multi loops understanding -the continuity principle

  • Temporal information recovery -the matching principle

  • Hidden loop tracking -an application to ascending (descending) loops

  • Hidden loop tracking -an application to ascending (descending) loops (cont.)

  • Hidden loop tracking -an application to ascending (descending) loops (cont.)

  • Hidden loop tracking -an application to ascending (descending) loops (cont.)ThresholdSmall LoopsNo LoopsTotal81802093896131209340

  • Multi loops understanding -a classifier of beginning a-sMore than 40 writers with 1-4 samples per writer.

  • Multi loops understanding -a classifier of beginning a-s