25.4.2.3 Font Recognition, Multiple Fonts, Script Type, etc.

Chapter Contents (Back)
Font Recognition. Multi-Font. Multi-Script.

Kopec, G.E.,
Least-squares font metric estimation from images,
IP(2), No. 4, October 1993, pp. 510-519.
IEEE DOI 0402
BibRef

Liu, C.N., and Shelton, G.L.,
An Experimental Investigation of a Mixed Font Print Recognition System,
TC(15), No. 6, December 1966, pp. 916-925. The IBM font recognition work using N-Tuples. BibRef 6612

Morris, R.A.[Robert A.],
Classification of digital typefaces using spectral signatures,
PR(25), No. 8, August 1992, pp. 869-876.
Elsevier DOI 0401
BibRef

Wang, J.[Jin], Jean, J.[Jack],
Resolving multifont character confusion with neural networks,
PR(26), No. 1, January 1993, pp. 175-187.
Elsevier DOI 0401
BibRef

Khoubyari, S., Hull, J.J.,
Font and Function Word Identification in Document Recognition,
CVIU(63), No. 1, January 1996, pp. 66-74.
DOI Link BibRef 9601

Augusteijn, M.F., Warrender, C.E.,
Image Indexing Applied to Typewriter Font Identification,
NeurCompApp(4), No. 4, 1996, pp. 209-217. 9701
BibRef

Krtolica, R.V.[Radovan V.], Malitsky, S.[Sofya],
Multifont optical character recognition using a box connectivity approach,
US_Patent5,539,840, 07/23/1996.
HTML Version. Features computed within the bounding rectangle. BibRef 9607

Krtolica, R.V.[Radovan V.], Melen, R.D.[Roger D.],
Image recognition through localized interpretation,
US_Patent6,259,814, Jul 10, 2001
WWW Link. OCR BibRef 0107

Krtolica, R.V.,
Learning Character Recognition by Localized Interpretation of Character-Images,
ICIP97(III: 292-295).
IEEE DOI BibRef 9700

Zramdini, A.[Abdelwahab], and Ingold, R.[Rolf],
Optical Font Recognition Using Typographical Features,
PAMI(20), No. 8, August 1998, pp. 877-882.
IEEE DOI BibRef 9808
Earlier:
ApOFIS: an A priori optical font identification system,
CIAP95(527-532).
Springer DOI 9509
Identify the font -- typeface, weight, slope and size -- not the characters. BibRef

Omachi, S.[Shin'ichiro], Inoue, M.[Masaki], Aso, H.[Hirotomo],
Structure Extraction from Decorated Characters Using Multiscale Images,
PAMI(23), No. 3, March 2001, pp. 315-322.
IEEE DOI 0103
BibRef
Earlier:
Structure Extraction from Various Kinds of Decorated Characters Using Multi-scale Images,
ICPR00(Vol IV: 455-458).
IEEE DOI 0009
Decorated characters: Fancy characters, not the ones in illuminated manuscripts. Multiscale images are used for structure extraction, then match on the character structure. BibRef

Iwamura, M., Negishi, K., Omachi, S., Aso, H.,
Isolated character recognition by searching feature points,
ICDAR05(II: 1035-1039).
IEEE DOI 0508
BibRef

Chaudhuri, B.B., Garain, U.,
Extraction of type style-based meta-information from imaged documents,
IJDAR(3), No. 3, 2001, pp. 138-149.
Springer DOI 0105
BibRef

Zhu, Y.[Yong], Tan, T.N.[Tie-Niu], Wang, Y.H.[Yun-Hong],
Font Recognition Based on Global Texture Analysis,
PAMI(23), No. 10, October 2001, pp. 1192-1200.
IEEE DOI 0110
Find the font from texture features, not analysis of individual characters. BibRef

Pal, U., Chaudhuri, B.B.,
Identification of different script lines from multi-script documents,
IVC(20), No. 13-14, December 2002, pp. 945-954.
Elsevier DOI 0212
BibRef
And: Correction: IVC(21), No. 11, October 2003, pp. 1017.
Elsevier DOI 0310
BibRef

Pal, U., Sinha, S., Chaudhuri, B.B.,
Multi-oriented English Text Line Identification,
SCIA03(1146-1153).
Springer DOI 0310
BibRef

Shivakumara, P.[Palaiahnakote], Yuan, Z.H.[Ze-Huan], Zhao, D.[Danni], Lu, T.[Tong], Tan, C.L.[Chew Lim],
New Gradient-Spatial-Structural Features for video script identification,
CVIU(130), No. 1, 2015, pp. 35-53.
Elsevier DOI 1411
Video text blocks BibRef

Yuan, Z.H.[Ze-Huan], Lu, T.[Tong], Tan, C.L.[Chew Lim],
Learning discriminated and correlated patches for multi-view object detection using sparse coding,
PR(69), No. 1, 2017, pp. 26-38.
Elsevier DOI 1706
Multi-view object detection BibRef

Shivakumara, P.[Palaiahnakote], Sharma, N.[Nabin], Pal, U.[Umapada], Blumenstein, M.[Michael], Tan, C.L.[Chew Lim],
Gradient-Angular-Features for Word-wise Video Script Identification,
ICPR14(3098-3103)
IEEE DOI 1412
Equations BibRef

Sharma, N., Chanda, S., Pal, U., Blumenstein, M.,
Word-Wise Script Identification from Video Frames,
ICDAR13(867-871)
IEEE DOI 1312
Zernike polynomials BibRef

Sinha, S.[Suranjit], Pal, U.[Umapada], Chaudhuri, B.B.,
Word-Wise Script Identification from Indian Documents,
DAS04(310-321).
Springer DOI 0505
BibRef

Pal, U., Sinha, S., Chaudhuri, B.B.,
Multi-script line identification from Indian documents,
ICDAR03(880-884).
IEEE DOI 0311
BibRef

Namboodiri, A.M.[Anoop M.], Jain, A.K.[Anil K.],
Online Handwritten Script Recognition,
PAMI(26), No. 1, January 2004, pp. 124-130.
IEEE Abstract. 0401
BibRef
Earlier:
On-line script recognition,
ICPR02(III: 736-739).
IEEE DOI 0211
Classify words and lines into Arabic, Cyrillic, Devnagari, Han, Hebrew, or Roman script. Use 11 spatial and temporal features for the strokes. Roughly 87% on words, 95% on 5-7 word lines. BibRef

Sarkar, P.[Prateek], Nagy, G.[George],
Style Consistent Classification of Isogenous Patterns,
PAMI(27), No. 1, January 2005, pp. 88-98.
IEEE Abstract. 0412
BibRef
Earlier:
Style-consistency in isogenous patterns,
ICDAR01(1169-1174).
IEEE DOI 0109
BibRef
And: A2, A1:
Document style census for OCR,
DIAL04(134-147).
IEEE DOI 0404
BibRef
Earlier:
Classification of Style-Constrained Pattern-Fields,
ICPR00(Vol II: 855-858).
IEEE DOI 0009
Classification by fields, i.e. a string is usually the same font. Extract regions of the same style (e.g. font).
See also Analytical Results on Style-Constrained Bayesian Classification of Pattern Fields. BibRef

Sarkar, P.[Prateek],
Image classification: Classifying distributions of visual features,
ICPR06(II: 472-475).
IEEE DOI 0609
BibRef

Sarkar, P.[Prateek],
An iterative algorithm for optimal style conscious field classification,
ICPR02(IV: 243-246).
IEEE DOI 0211
BibRef

Avilés-Cruz, C.[Carlos], Rangel-Kuoppa, R.[Risto], Reyes-Ayala, M.[Mario], Andrade-Gonzalez, A., Escarela-Perez, R.[Rafael],
High-order statistical texture analysis--font recognition applied,
PRL(26), No. 2, 15 January 2005, pp. 135-145.
Elsevier DOI 0501
Identify the font from texture. BibRef

Busch, A.[Andrew], Boles, W.W.[Wageeh W.], Sridharan, S.[Sridha],
Texture for Script Identification,
PAMI(27), No. 11, November 2005, pp. 1720-1732.
IEEE DOI 0510
BibRef

Busch, A.[Andrew],
Multi-font Script Identification Using Texture-Based Features,
ICIAR06(II: 844-852).
Springer DOI 0610
BibRef

Ding, X.Q.[Xiao-Qing], Chen, L.[Li], Wu, T.[Tao],
Character Independent Font Recognition on a Single Chinese Character,
PAMI(29), No. 2, February 2007, pp. 195-204.
IEEE DOI 0701
Font recognition for any unknown Chinese Character. Font recognition improves with multiple characters. BibRef

Joshi, G.D.[Gopal Datt], Garg, S.[Saurabh], Sivaswamy, J.[Jayanthi],
A generalised framework for script identification,
IJDAR(10), No. 2, November 2007, pp. 55-68.
Springer DOI 0711
BibRef
Earlier:
Script Identification from Indian Documents,
DAS06(255-267).
Springer DOI 0602
BibRef

Hiremath, P.S., Shivashankar, S.,
Wavelet based co-occurrence histogram features for texture classification with an application to script identification in a document image,
PRL(29), No. 9, 1 July 2008, pp. 1182-1189.
Elsevier DOI 0711
Wavelet transform; Texture features; Texture classification; Script identification; Document image; Gabor filters BibRef

Pati, P.B.[Peeta Basa], Ramakrishnan, A.G.,
Word level multi-script identification,
PRL(29), No. 9, 1 July 2008, pp. 1218-1229.
Elsevier DOI 0711
Gabor filter; DCT; Script identification BibRef

Ghosh, D.[Debashis], Dube, T.[Tulika], Shivaprasad, A.[Adamane],
Script Recognition: A Review,
PAMI(32), No. 12, December 2010, pp. 2142-2161.
IEEE DOI 1011
Survey, Script Recognition. Identify the script before recognition. BibRef

Kae, A.[Andrew], Smith, D.A.[David A.], Learned-Miller, E.G.[Erik G.],
Learning on the Fly: A Font-Free Approach Toward Multilingual OCR,
IJDAR(14), No. 3, September 2011, pp. 289-301.
WWW Link. 1109
BibRef
Earlier: A1, A3, only:
Learning on the Fly: Font-Free Approaches to Difficult OCR Problems,
ICDAR09(571-575).
IEEE DOI 0907
BibRef

Solli, M.[Martin], Lenz, R.[Reiner],
A Font Search Engine for Large Font Databases,
ELCVIA(10), No. 1, 2011, pp. xx-yy.
DOI Link 1112
BibRef
Earlier:
FyFont: Find-your-Font in Large Font Databases,
SCIA07(432-441).
Springer DOI 0706
BibRef

Alabert, A.[Aureli], Rangel, L.M.[Luz Ma.],
Classifying the typefaces of the Gutenberg 42-line bible,
IJDAR(14), No. 4, December 2011, pp. 303-317.
WWW Link. 1112
BibRef

Zagoris, K.[Konstantinos], Pratikakis, I.[Ioannis], Antonacopoulos, A.[Apostolos], Gatos, B.[Basilis], Papamarkos, N.[Nikos],
Distinction between handwritten and machine-printed text based on the bag of visual words model,
PR(47), No. 3, 2014, pp. 1051-1062.
Elsevier DOI 1312
Bag of visual words BibRef

Kacem, A.[Afef], Saidani, A.[Asma], Belaid, A.[Abdel],
How to separate between Machine-Printed/Handwritten and Arabic/Latin Words?,
ELCVIA(13), No. 1, 2014, pp. xx-yy.
DOI Link 1405
BibRef

Saidani, A., Echi, A.K., Belaid, A.,
Identification of Machine-Printed and Handwritten Words in Arabic and Latin Scripts,
ICDAR13(798-802)
IEEE DOI 1312
Bayes methods BibRef

Saidani, A.[Asma], Kacem, A.[Afef], Belaid, A.[Abdel],
Arabic/Latin and Machine-printed/Handwritten Word Discrimination using HOG-based Shape Descriptor,
ELCVIA(14), No. 2, 2015, pp. xx-yy.
DOI Link 1601
BibRef
Earlier:
Co-occurrence Matrix of Oriented Gradients for word script and nature identification,
ICDAR15(16-20)
IEEE DOI 1511
AODEsr BibRef

Bozkurt, A.[Alican], Duygulu, P.[Pinar], Cetin, A.E.[A. Enis],
Classifying fonts and calligraphy styles using complex wavelet transform,
SIViP(9), No. 1 Supp, December 2015, pp. 225-234.
WWW Link. 1601
BibRef

Arabnejad, E.[Ehsan], Moghaddam, R.F.[Reza Farrahi], Cheriet, M.[Mohamed],
PSI: Patch-Based Script Identification Using Non-Negative Matrix Factorization,
PR(67), No. 1, 2017, pp. 328-339.
Elsevier DOI 1704
Script identification BibRef

Han, X.K.[Xing-Kun], Aysa, A.[Alimjan], Mamat, H.[Hornisa], Yadikar, N.[Nurbiya], Ubul, K.[Kurban],
Script Identification of Central Asia Based on Fused Texture Features,
ICPR18(3675-3680)
IEEE DOI 1812
Feature extraction, Support vector machines, Transforms, Gray-scale, Kernel, Data mining, Filter banks, script identification, support vector machine BibRef

Jiang, S., Wang, Z., Hertzmann, A., Jin, H., Fu, Y.,
Visual Font Pairing,
MultMed(22), No. 8, August 2020, pp. 2086-2097.
IEEE DOI 2007
Portable document format, Visualization, Task analysis, Layout, Measurement, Internet, Training, Font, pairing, recommendation, metric learning BibRef

Cheikhrouhou, A.[Ahmed], Kessentini, Y.[Yousri], Kanoun, S.[Slim],
Multi-task learning for simultaneous script identification and keyword spotting in document images,
PR(113), 2021, pp. 107832.
Elsevier DOI 2103
CBP, CTC, Keyword spotting, Script identification, Handwritten BibRef

Li, X.M.[Xiao-Meng], Zhan, H.J.[Hong-Jian], Shivakumara, P.[Palaiahnakote], Pal, U.[Umapada], Lu, Y.[Yue],
SANet-SI: A new Self-Attention-Network for Script Identification in scene images,
PRL(171), 2023, pp. 45-52.
Elsevier DOI 2306
Script identification, Feature fusion, Language identification BibRef

Yuan, H.H.[Hong-Hui], Yanai, K.J.[Kei-Ji],
Multi-Style Shape Matching GAN for Text Images,
IEICE(E108-D), No. 4, April 2024, pp. 505-514.
WWW Link. 2404
BibRef

Kang, J.[Jihun], Haraguchi, D.[Daichi], Matsuda, S.[Seiya], Kimura, A.[Akisato], Uchida, S.[Seiichi],
Shared Latent Space of Font Shapes and Their Noisy Impressions,
MMMod22(II:146-157).
Springer DOI 2203
BibRef

Shimoda, W.[Wataru], Haraguchi, D.[Daichi], Uchida, S.[Seiichi], Yamaguchi, K.[Kota],
De-rendering Stylized Texts,
ICCV21(1056-1065)
IEEE DOI 2203
Editing appearance of text. Graphics, Image resolution, Web pages, Media, Rendering (computer graphics), Task analysis, Scene analysis and understanding BibRef