Large-Scale Polytonic Greek OCR - e-Humanities Home

Large-Scale PolytonicGreek OCRIn Practice and Theory: Back endProf. Bruce Robertson, Head, Dept. of ClassicsMount Allison University, New Brunswick CanadaUniversität LeipzigOct 10, 2012

Why Ancient Greek OCR?1.Rapid digitization of Greek texts not yet indigital libraries

Why Ancient Greek OCR?1.Rapid digitization of Greek texts not yet indigital libraries2.Study of textual variants and app. crit.

Why Ancient Greek OCR?1.Rapid digitization of Greek texts not yet indigital libraries2.Study of textual variants and app. crit.3.Text reuse analysis, e.g:lYou are reading Aesch. Agamemnon 120

Why Ancient Greek OCR?1.Rapid digitization of Greek texts not yet indigital libraries2.Study of textual variants and app. crit.3.Text reuse analysis, e.g:lYou are reading Aesch. Agamemnon 120lWhere is this passage quoted in:

Why Ancient Greek OCR?1.Rapid digitization of Greek texts not yet indigital libraries2.Study of textual variants and app. crit.3.Text reuse analysis, e.g:lYou are reading Aesch. Agamemnon 120lWhere is this passage quoted in:l Phoenix

Why Ancient Greek OCR?1.Rapid digitization of Greek texts not yet indigital libraries2.Study of textual variants and app. crit.3.Text reuse analysis, e.g:lYou are reading Aesch. Agamemnon 120lWhere is this passage quoted in:l Phoenixl E.R. Dodds

Why Ancient Greek OCR?1.Rapid digitization of Greek texts not yet indigital libraries2.Study of textual variants and app. crit.3.Text reuse analysis4.General searching

Why Ancient Greek OCR?1.Rapid digitization of Greek texts not yet indigital libraries2.Study of textual variants and app. crit.3.Text reuse analysis4.General searchinglMorphologically aware, and using the pageimage

Out-of-the-box OCR Engines?10 XOPIKIOItgsh; (')lauTOU hoaschmtEros efzfovsi , xaOairep tbv PoHe|/.sha) Tov HEVoxpotTi] (*) irpo

What Makes Greek OCR Hard?

Unusual CharactersἘν ἀρχῇ ἦν ὁ Λόγος,καὶ ὁ Λόγος ἦν πρὸς τὸν Θεόν,καὶ Θεὸς ἦν ὁ Λόγος.

AccentsἘν ἀρχῇ ἦν ὁ Λόγος,καὶ ὁ Λόγος ἦν πρὸς τὸν Θεόν,καὶ Θεὸς ἦν ὁ Λόγος.

Smooth and Rough Breathing MarksἘν ἀρχῇ ἦν ὁ Λόγος,καὶ ὁ Λόγος ἦν πρὸς τὸν Θεόν,καὶ Θεὸς ἦν ὁ Λόγος.

Iota SubscriptἘν ἀρχῇ ἦν ὁ Λόγος,καὶ ὁ Λόγος ἦν πρὸς τὸν Θεόν,καὶ Θεὸς ἦν ὁ Λόγος.

Diversity of 19th Century Fonts

Unusual Typesetting

Unusual Typesetting

Ordering of Charactersprint unicode(u"\N{GREEK CAPITAL LETTER IOTA}\N{COMBINING COMMA ABOVE}\N{COMBINING ACUTE ACCENT}\N{GREEK SMALL LETTER ALPHA}").encode('utf-8')Ἴδ

MethodDalitz and Brandt provide an experimental framework forGreek OCR work using Gamera engineTo which I added:- splitting- grouping- SQL output- HOCR output- hocr (layout) input

Method160 Greek-heavy texts chosen from Google's Latinand Greek collection at 300 dpiOf these, random samples of 10 pages were takenEach was processed with each of the 20 classifiersmade in summer of 2011 by undergraduate studentsUsing:Boschetti’s ground-truth-less Greek text evaluatorAtlantic Computational Excellence Network, AtlanticCanada’s parallel computing network

Challenge I: Glyph Recognition

ΕΚ ΤΟΥ Λἀλλά τι καὶ χλεύης οἶνος ἴχειν ἐθἐλει· —οὐδὲν ἀπόβλητον Διονύσιον, οὐδὲ γίγαρτον,ὁ Κεῖός φησι ποιητής (h·. 88 B4)·59. τῶν οἴνων ὃ μὲν λευκός, ὃ δὲ κιρρός, ὃ δὲμἐλας· καὶ ὁ μὲν λευκὸς λεπτότατος τῇ φύσει, οὐρητικός,θερμὸς πεπτικός τε ω’·ν τὴν κεφαλὴν ποιεῖ διά.πυρον· ἀνωφερὴς γὰρ ὁ οἶνος. ὁ δὲ μέλας, ὁ μὴ γλυκάζων,τροφιμώτατος, στυπτικός. ὁ δὲ γλυκάζων καὶτῶν λεmῶν καὶ τῶν κιρρῶν τροφιμώτατος. λεαίνει

MethodOCRφωνό1υς φασὶ καὶαὐτ0ὺς διὰ τὴυ πάυυτρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶοὐτ0ι ἐσθητῖ πολυτελεῖἐθρύπτοντ0,καὶ τραπίζηςἀσωτίά καὶ ὑπλρ τὴνχρει.αν

MethodOCRφωνό1υς φασὶ καὶαὐτ0ὺς διὰ τὴυ πάυυτρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶοὐτ0ι ἐσθητῖ πολυτελεῖἐθρύπτοντ0,καὶ τραπίζηςἀσωτίά καὶ ὑπλρ τὴνχρει.ανφωνθυς φασὶ καὶαὐτοὺς διὰ τὴνπάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοικαὶ ουrτοι ἐσθητῖπολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶὑπὲρ τὴν χρείᾳν

φωνθυς φασὶ καὶαὐτοὺς διὰ τὴνπάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοικαὶ ουrτοι ἐσθητῖπολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶὑπὲρ τὴν χρείᾳν.....MethodOCRφωνό1υς φασὶ καὶαὐτ0ὺς διὰ τὴυ πάυυτρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶοὐτ0ι ἐσθητῖ πολυτελεῖἐθρύπτοντ0,καὶ τραπίζηςἀσωτίά καὶ ὑπλρ τὴνχρει.αν

φωνθυς φασὶ καὶαὐτοὺς διὰ τὴνπάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοικαὶ ουrτοι ἐσθητῖπολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶὑπὲρ τὴν χρείᾳν.....MethodOCRφωνό1υς φασὶ καὶαὐτ0ὺς διὰ τὴυ πάυυτρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶοὐτ0ι ἐσθητῖ πολυτελεῖἐθρύπτοντ0,καὶ τραπίζηςἀσωτίά καὶ ὑπλρ τὴνχρει.αν

MethodOCRφωνό1υς φασὶ καὶαὐτ0ὺς διὰ τὴυ πάυυτρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶοὐτ0ι ἐσθητῖ πολυτελεῖἐθρύπτοντ0,καὶ τραπίζηςἀσωτίά καὶ ὑπλρ τὴνχρει.ανφωνθυς φασὶ καὶαὐτοὺς διὰ τὴνπάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοικαὶ ουrτοι ἐσθητῖπολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶὑπὲρ τὴν χρείᾳν.....0.370.44

MethodOCRφωνό1υς φασὶ καὶαὐτ0ὺς διὰ τὴυ πάυυτρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶοὐτ0ι ἐσθητῖ πολυτελεῖἐθρύπτοντ0,καὶ τραπίζηςἀσωτίά καὶ ὑπλρ τὴνχρει.ανφωνθυς φασὶ καὶαὐτοὺς διὰ τὴνπάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοικαὶ ουrτοι ἐσθητῖπολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶὑπὲρ τὴν χρείᾳν.....0.370.44This is our statusas of January2012

MethodOCRφωνό1υς φασὶ καὶαὐτ0ὺς διὰ τὴυ πάυυτρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶοὐτ0ι ἐσθητῖ πολυτελεῖἐθρύπτοντ0,καὶ τραπίζηςἀσωτίά καὶ ὑπλρ τὴνχρει.ανφωνθυς φασὶ καὶαὐτοὺς διὰ τὴνπάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοικαὶ ουrτοι ἐσθητῖπολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶὑπὲρ τὴν χρείᾳν.....0.37Spell-checkand alignment0.44

MethodOCRφωνό1υς φασὶ καὶαὐτ0ὺς διὰ τὴυ πάυυτρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶοὐτ0ι ἐσθητῖ πολυτελεῖἐθρύπτοντ0,καὶ τραπίζηςἀσωτίά καὶ ὑπλρ τὴνχρει.ανφωνθυς φασὶ καὶαὐτοὺς διὰ τὴνπάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοικαὶ ουrτοι ἐσθητῖπολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶὑπὲρ τὴν χρείᾳν.....0.37Spell-checkand alignment0.44φωνθυς φασὶ καὶαὐτοὺς διὰ τὴνπάνυ τρυφὴν ἀπολέσθαι.καὶ γάρ τοικαὶ οὗτοι ἐσθητῖπολυτελεῖ ἐθρύπτοντο,καὶτραπέζης ἀσωτίᾳκαὶ ὑπὲρ τὴνχρείᾳν



Method: Parallel Processingφωνό1υς φασὶ καὶ αὐτ0ὺς διὰ τὴυ πάυυ τρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶ οὐτ0ι ἐσθητῖ πολυτελεῖ ἐθρύπτοντ0,καὶ τραπίζης ἀσωτίά καὶ ὑπλρ τὴν χρει.ανOCRφωνό1υς φασὶ καὶ αὐτ0ὺς διὰ τὴυ πάυυ τρυφὴν ἀπο-0.37λέσθαι. καὶ γάρ τοι καὶ οὐτ0ι ἐσθητῖ πολυτελεῖ ἐθρύπτοντ0,καὶ τραπίζης ἀσωτίά καὶ ὑπλρ τὴν χρει.ανφωνθυς φασὶ καὶ αὐτοὺς διὰ τὴν πάνυ τρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶ οὗτοι ἐσθητῖ πολυτελεῖ ἐθρύπτοντο,καὶ τραπέζης ἀσωτίᾳ 0.37 καὶ ὑπὲρ τὴν χρείᾳνSpell-check φωνό1υς φασὶ καὶ αὐτ0ὺς διὰ τὴυ πάυυ τρυφὴν ἀποandalignmentλέσθαι. καὶ γάρ τοι φωνθυς καὶ οὐτ0ι φασὶ ἐσθητῖ καὶ αὐτοὺς πολυτελεῖ διὰ τὴν ἐθρύ- πάνυ τρυφὴν ἀπο-φωνθυς φασὶ καὶ αὐτοὺς διὰ τὴν πάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοι καὶ ουrτοι ἐσθητῖ πολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶ ὑπὲρ τὴν χρείᾳνOCRφωνθυς φασὶ καὶ αὐτοὺς διὰ τὴν πάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοι 0.44 καὶ ουrτοι ἐσθητῖ πολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶ ὑπὲρ τὴν χρείᾳνπτοντ0, καὶ τραπίζης ἀσωτίά καὶ ὑπλρ τὴν χρει.ανλέσθαι. καὶ γάρ τοι καὶ οὗτοι ἐσθητῖ πολυτελεῖ ἐθρύπτοντο,καὶ τραπέζης ἀσωτίᾳ καὶ ὑπὲρ τὴν χρείᾳνSpell-checkand alignment0.37φωνό1υς φασὶ καὶ αὐτ0ὺς φωνθυς διὰ φασὶ τὴυ πάυυ καὶ αὐτοὺς τρυφὴν διὰ ἀπο- τὴν πάνυ τρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶ λέσθαι. οὐτ0ι ἐσθητῖ καὶ γάρ πολυτελεῖ τοι καὶ οὗτοι ἐθρύ- ἐσθητῖ πολυτελεῖ ἐθρύπτοντ0,καὶ τραπίζης πτοντο, ἀσωτίά καὶ ὑπλρ τραπέζης τὴν χρει.αν ἀσωτίᾳ καὶ ὑπὲρ τὴν χρείᾳνSpell-checkOCR0.44and alignmentφωνθυς φασὶ καὶ αὐτοὺς διὰ τὴν πάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοι καὶ ουrτοι ἐσθητῖ πολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶ ὑπὲρ τὴν χρείᾳνOCR0.440.37φωνθυς φασὶ καὶ αὐτοὺς διὰ τὴν πάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοι καὶ ουrτοι ἐσθητῖ πολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶ ὑπὲρ τὴν χρείᾳνφωνό1υς φασὶ καὶ αὐτ0ὺς διὰ τὴυ πάυυ τρυφὴν ἀπολέσθαι.φωνθυς καὶ γάρ φασὶ τοι καὶ καὶ οὐτ0ι αὐτοὺς ἐσθητῖ διὰ τὴν πολυτελεῖ πάνυ τρυφὴν ἐθρύ- ἀποπτοντ0,λέσθαι. καὶ τραπίζης καὶ γάρ ἀσωτίά τοι καὶ οὗτοι καὶ ὑπλρ ἐσθητῖ τὴν πολυτελεῖ χρει.αν ἐθρύπτοντο,καὶ τραπέζης ἀσωτίᾳ καὶ ὑπὲρ τὴν χρείᾳνSpell-checkand alignment0.37OCR0.44φωνθυς φασὶ καὶ αὐτοὺς διὰ τὴν πάνυ τρυφὴν ἀπολέσθαι. καὶ γάρ τοι καὶ ουrτοι ἐσθητῖ πολυτελεῖ c̓̔θρύπτοντο,καὶ τραπe-́ζης ἀσωτίᾳ καὶ ὑπὲρ τὴν χρείᾳνφωνθυς φασὶ καὶ αὐτοὺς διὰ τὴν πάνυ τρυφὴν ἀπολέσθαι.καὶ γάρ τοι καὶ οὗτοι ἐσθητῖ πολυτελεῖ ἐθρύπτοντο,καὶ τραπέζης ἀσωτίᾳ καὶ ὑπὲρ τὴν χρείᾳνSpell-checkand alignment0.44

Challenge II: Line Segmentation

Failed Line Segmentation

Resulting OCR●π̀ ππ πτ ππ π͂π πσ π π πτ ππ ππ ππ τπτπ ππ τΣm ππ τ πτ τπ ππ ππ ππ ππ πτπτ ππ αα ππ ππ͂ π

πυρον· ἀνωφερὴς γὰρ ὁ οἶνος. ὁ δὲ μέλας, ὁ μὴ γλυκάζων,τροφιμώτατος, στυπτικός. ὁ δὲ γλυκάζων καὶτῶν λεmῶν καὶ τῶν κιρρῶν τροφιμώτατος. λεαίνειὲ ? ξ l · . v A ε ἰ 1 . t σ d h ι 1 · t e 1 C n a S χ e c λ 1 h · ε wυ 2 é η s 4 t ς κ B ε κ e 2 ο r g 6 ι ν ο k ω π ὔ . . ν δ ε λ η τ ὲε τ ν κ υ ι έ γ χͅ S ο η C c ς̀ ς h s C w C u p Ε . · rͅ . a ο υ ' d 1v

Tesseract's Line Segmentation

Click to add titleImproved Outputκeνθερός ¹8², ²5.πε.νθος.̓²7, ¹o. .̓͂s9, ¹².π’νἱα ¹8², ,̀4.noL .̀35.πι’νω ¹34, 4.πἱoς ¹⁴.̀, 3¹.πεπάλη I²6,¹4. ²Ω, 35.πιπιθών 55̀ ²,̓ .πέπλος ¹x5, ²2.πνρίνηλα S4, ²7.τιρίκυφον γκπωμα s̀,́ ¹S,π,ριπατος ¹57̀ 6.περιστερά ¹s-́͂ -͂.̓.πsρίττωμα ³̀q, 4.πsρόνη ¹a8́ 4.πεσε͂ͅ νI3²́ a5.͂αἑσκος ¹³o̓́ 8·αεσσὰ etπισσο ί.̀²6, 5ὶπισσός .̓5á a4,

Infrastructure●Sun Grid Engine and bash scripts piping:●●●Image magickpythonjava

Infrastructure●●●Sun Grid Engine and bash scripts piping:●●●Image magickpythonjavaBetween 20 and 60 seconds per page percoreAlong what parameters must we multiply ourefforts?

Scores0.60.50.40.30.20.100EQOAAAAYAAJ0qBEAAAAMAAJ0xcOAAAAYAAJ14lfAAAAMAAJTeubner_SlimTeubner_Similar2Teubner_SimilarTeubner_SansSerifTeubner_LatinSuper_Swirly2Super_SwirlySmythOxfordOribase_TestOribase_Font_2Oribase_Font_1Oribase_FontNew_TeubnerLoeb_WholisticLittreLexiconKurkegamera-greekocr-training-loeb-separatistic-2011-04-25EtymologicumEarly_TeubnerCambridge

Another Dimension: Image Threshold

Choosing Best ClassifierTwo approaches explored:

Choosing Best ClassifierTwo approaches explored:1.Sampling

Choosing Best ClassifierTwo approaches explored:1.Sampling2.A Naive Bayesian classifier using our sampledata

Choosing An OCR Classifier WithMachine LearningTypeface is related to:

Choosing An OCR Classifier WithMachine LearningTypeface is related to:•publication house

Choosing An OCR Classifier WithMachine LearningTypeface is related to:•publication house•date

Choosing An OCR Classifier WithMachine LearningTypeface is related to:•publication house•date•author

Choosing An OCR Classifier WithMachine LearningTypeface is related to:•publication house•date•authorWe have these metadata, and we have theBoschetti-scores of results!

Method•Regularized publisher name•Cleaned dates•Randomly divided 150 books into training setand result set•Used Natural Language Toolkit'sNaiveBayesClassifier to predict best classifier

ResultAbout 50% success

ResultAbout 50% success... but wait ...

ResultAbout 50% success... but wait ...Success doesn't matter as much as averageBoschetti-score, after all:

ResultAbout 50% success... but wait ...Success doesn't matter as much as averageBoschetti-score, after all:•Some texts are a mess

ResultAbout 50% success... but wait ...Success doesn't matter as much as averageBoschetti-score, after all:•Some texts are a mess•Many have very close-scoring 1st and 2ndplace classifiers

ResultBest average score:0.38

ResultBest average score:0.38Average score that would have resulted if theOCR classifier chosen by NLTK were used:0.33

ResultBest average score:0.38Average score that would have resulted if theOCR classifier chosen by NLTK were used:0.33Much better than 50%, and a promising start

What is Our Corpus?

600 and 300 PPI Images

600 and 300 PPI Images

Challenge: Classifiers that areindependent of glyph size

Very High Quality Single Texts●Such as Kaibel edition of Deipnosophistai

Very High Quality Single Texts●Such as Kaibel edition of Deipnosophistai●Work up a single, best, classifier

Very High Quality Single Texts●Such as Kaibel edition of Deipnosophistai●●Work up a single, best, classifierImprove results on other axes

Very High Quality Single Texts●Such as Kaibel edition of Deipnosophistai●●Work up a single, best, classifierImprove results on other axes– E.g. image threshold

Current Work: Pre-post-processing●●●Distinguishing comma, smooth breathingand apostrophe by order in data streamusing regexes:E.g. consonant + smooth breathing + endof word -> consonant + apostropheLayout analysis would be more powerful

Future Challenges: EducationalCollaboration with UndergraduatesHard: Using near-complete OCR edition forclassroom, correcting it along the way?Easy: A mobile app. for choosing the correctreadingEasiest: A mobile app. to help train an OCRengine recognize Greek letters among Latinones

Future Challenges: Specialized LineSegmentation Algorithm1Identify glyphs2Organize all ε,ν,ι,α, etc. according to bottomedge3Organize those with descenders4Group with these, iota subscripts below andother diacritics above

Future Challenges: A MorphologicallyAware, Image Fronted Search Engine

Thanks●●●●Compute CanadaSocial Sciences and Humanities ResearchCouncil of CanadaNew Brunswick Innovation FoundationPresident's Research Fund, Mount AllisonUniversity

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