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Author |
Alicia Fornes; Beata Megyesi; Joan Mas |
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Title |
Transcription of Encoded Manuscripts with Image Processing Techniques |
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Conference Article |
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Year |
2017 |
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Digital Humanities Conference |
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441-443 |
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DH |
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DAG; 600.097; 600.121 |
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no |
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Admin @ si @ FMM2017 |
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3061 |
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Author |
Kaida Xiao; Chenyang Fu; Dimosthenis Karatzas; Sophie Wuerger |
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Title |
Visual Gamma Correction for LCD Displays |
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Journal Article |
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Year |
2011 |
Publication |
Displays |
Abbreviated Journal |
DIS |
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Volume |
32 |
Issue |
1 |
Pages |
17-23 |
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Keywords |
Display calibration; Psychophysics ; Perceptual; Visual gamma correction; Luminance matching; Observer-based calibration |
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Abstract |
An improved method for visual gamma correction is developed for LCD displays to increase the accuracy of digital colour reproduction. Rather than utilising a photometric measurement device, we use observ- ers’ visual luminance judgements for gamma correction. Eight half tone patterns were designed to gen- erate relative luminances from 1/9 to 8/9 for each colour channel. A psychophysical experiment was conducted on an LCD display to find the digital signals corresponding to each relative luminance by visually matching the half-tone background to a uniform colour patch. Both inter- and intra-observer vari- ability for the eight luminance matches in each channel were assessed and the luminance matches proved to be consistent across observers (DE00 < 3.5) and repeatable (DE00 < 2.2). Based on the individual observer judgements, the display opto-electronic transfer function (OETF) was estimated by using either a 3rd order polynomial regression or linear interpolation for each colour channel. The performance of the proposed method is evaluated by predicting the CIE tristimulus values of a set of coloured patches (using the observer-based OETFs) and comparing them to the expected CIE tristimulus values (using the OETF obtained from spectro-radiometric luminance measurements). The resulting colour differences range from 2 to 4.6 DE00. We conclude that this observer-based method of visual gamma correction is useful to estimate the OETF for LCD displays. Its major advantage is that no particular functional relationship between digital inputs and luminance outputs has to be assumed. |
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Elsevier |
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no |
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Admin @ si @ XFK2011 |
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1815 |
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Author |
C. Alejandro Parraga; Jordi Roca; Dimosthenis Karatzas; Sophie Wuerger |
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Title |
Limitations of visual gamma corrections in LCD displays |
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Journal Article |
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Year |
2014 |
Publication |
Displays |
Abbreviated Journal |
Dis |
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Volume |
35 |
Issue |
5 |
Pages |
227–239 |
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Keywords |
Display calibration; Psychophysics; Perceptual; Visual gamma correction; Luminance matching; Observer-based calibration |
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Abstract |
A method for estimating the non-linear gamma transfer function of liquid–crystal displays (LCDs) without the need of a photometric measurement device was described by Xiao et al. (2011) [1]. It relies on observer’s judgments of visual luminance by presenting eight half-tone patterns with luminances from 1/9 to 8/9 of the maximum value of each colour channel. These half-tone patterns were distributed over the screen both over the vertical and horizontal viewing axes. We conducted a series of photometric and psychophysical measurements (consisting in the simultaneous presentation of half-tone patterns in each trial) to evaluate whether the angular dependency of the light generated by three different LCD technologies would bias the results of these gamma transfer function estimations. Our results show that there are significant differences between the gamma transfer functions measured and produced by observers at different viewing angles. We suggest appropriate modifications to the Xiao et al. paradigm to counterbalance these artefacts which also have the advantage of shortening the amount of time spent in collecting the psychophysical measurements. |
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CIC; DAG; 600.052; 600.077; 600.074 |
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no |
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Admin @ si @ PRK2014 |
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2511 |
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Author |
Pau Torras; Mohamed Ali Souibgui; Sanket Biswas; Alicia Fornes |
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Title |
Segmentation-Free Alignment of Arbitrary Symbol Transcripts to Images |
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Conference Article |
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Year |
2023 |
Publication |
Document Analysis and Recognition – ICDAR 2023 Workshops |
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Volume |
14193 |
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Pages |
83-93 |
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Historical Manuscripts; Symbol Alignment |
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Abstract |
Developing arbitrary symbol recognition systems is a challenging endeavour. Even using content-agnostic architectures such as few-shot models, performance can be substantially improved by providing a number of well-annotated examples into training. In some contexts, transcripts of the symbols are available without any position information associated to them, which enables using line-level recognition architectures. A way of providing this position information to detection-based architectures is finding systems that can align the input symbols with the transcription. In this paper we discuss some symbol alignment techniques that are suitable for low-data scenarios and provide an insight on their perceived strengths and weaknesses. In particular, we study the usage of Connectionist Temporal Classification models, Attention-Based Sequence to Sequence models and we compare them with the results obtained on a few-shot recognition system. |
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LNCS |
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ICDAR |
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DAG |
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no |
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Admin @ si @ TSS2023 |
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3850 |
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Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |
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Title |
16th International Conference, 2021, Proceedings, Part III |
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Book Whole |
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Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
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12823 |
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This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
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Lausanne, Switzerland, September 5-10, 2021 |
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Springer Cham |
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Josep Llados; Daniel Lopresti; Seiichi Uchida |
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LNCS |
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978-3-030-86333-3 |
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ICDAR |
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DAG |
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no |
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Admin @ si @ |
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3727 |
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Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |
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Title |
16th International Conference, 2021, Proceedings, Part IV |
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Book Whole |
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2021 |
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Document Analysis and Recognition – ICDAR 2021 |
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12824 |
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Abstract |
This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
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Lausanne, Switzerland, September 5-10, 2021 |
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Springer Cham |
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Josep Llados; Daniel Lopresti; Seiichi Uchida |
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LNCS |
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978-3-030-86336-4 |
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ICDAR |
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DAG |
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no |
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Admin @ si @ |
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3728 |
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Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |
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Title |
16th International Conference, 2021, Proceedings, Part I |
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Book Whole |
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Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
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12821 |
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This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: historical document analysis, document analysis systems, handwriting recognition, scene text detection and recognition, document image processing, natural language processing (NLP) for document understanding, and graphics, diagram and math recognition. |
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Lausanne, Switzerland, September 5-10, 2021 |
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Springer Cham |
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Josep Llados; Daniel Lopresti; Seiichi Uchida |
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LNCS |
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978-3-030-86548-1 |
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ICDAR |
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DAG |
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no |
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Admin @ si @ |
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3725 |
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Author |
Josep Llados; Daniel Lopresti; Seiichi Uchida (eds) |
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Title |
16th International Conference, 2021, Proceedings, Part II |
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Book Whole |
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Year |
2021 |
Publication |
Document Analysis and Recognition – ICDAR 2021 |
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12822 |
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Abstract |
This four-volume set of LNCS 12821, LNCS 12822, LNCS 12823 and LNCS 12824, constitutes the refereed proceedings of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland in September 2021. The 182 full papers were carefully reviewed and selected from 340 submissions, and are presented with 13 competition reports.
The papers are organized into the following topical sections: document analysis for literature search, document summarization and translation, multimedia document analysis, mobile text recognition, document analysis for social good, indexing and retrieval of documents, physical and logical layout analysis, recognition of tables and formulas, and natural language processing (NLP) for document understanding. |
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Lausanne, Switzerland, September 5-10, 2021 |
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Springer Cham |
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Josep Llados; Daniel Lopresti; Seiichi Uchida |
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LNCS |
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978-3-030-86330-2 |
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ICDAR |
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DAG |
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no |
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Admin @ si @ |
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3726 |
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Author |
Mickael Coustaty; Alicia Fornes |
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Title |
Document Analysis and Recognition – ICDAR 2023 Workshops |
Type |
Book Whole |
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Year |
2023 |
Publication |
Document Analysis and Recognition – ICDAR 2023 Workshops |
Abbreviated Journal |
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14194 |
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2 |
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San Jose; USA; August 2023 |
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ICDAR |
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DAG |
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Admin @ si @ CoF2023 |
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3852 |
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Author |
Ernest Valveny; Philippe Dosch |
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Title |
Performance Evaluation of Symbol Recognition |
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Book Chapter |
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Year |
2004 |
Publication |
Document Analysis Systems |
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LNCS |
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3163 |
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354–365 |
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Springer-Verlag |
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S. Marinai, A. Dengel (Eds.), |
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3-540-23060-2 |
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DAG |
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DAG @ dag @ VaD2004a |
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502 |
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