Transfer Learning for OCRopus Model Training on Early Printed Books

A method is presented that significantly reduces the character error rates for OCR text obtained from OCRopus models trained on early printed books when only small amounts of diplomatic transcriptions are available. This is achieved by building from already existing models during training instead of starting from scratch. To overcome the discrepancies between the set of characters of the pretrained model and the additional ground truth the OCRopus code is adapted to allow for alphabet expansion or reduction. The character set is now capable of flexibly adding and deleting characters from the pretrained alphabet when an existing model is loaded. For our experiments we use a self-trained mixed model on early Latin prints and the two standard OCRopus models on modern English and German Fraktur texts. The evaluation on seven early printed books showed that training from the Latin mixed model reduces the average amount of errors by 43% and 26%, respectively compared to training from scratch with 60 and 150 lines of ground truth, respectively. Furthermore, it is shown that even building from mixed models trained on data unrelated to the newly added training and test data can lead to significantly improved recognition results

Partitioning of the Degradation Space for OCR Training

Generally speaking optical character recognition algorithms tend to perform better when presented with homogeneous data. This paper studies a method that is designed to increase the homogeneity of training data, based on an understanding of the types of degradations that occur during the printing and scanning process, and how these degradations affect the homogeneity of the data. While it has been shown that dividing the degradation space by edge spread improves recognition accuracy over dividing the degradation space by threshold or point spread function width alone, the challenge is in deciding how many partitions and at what value of edge spread the divisions should be made. Clustering of different types of character features, fonts, sizes, resolutions and noise levels shows that edge spread is indeed shown to be a strong indicator of the homogeneity of character data clusters

Escritoire: A Multi-touch Desk with e-Pen Input for Capture, Management and Multimodal Interactive Transcription of Handwritten Documents

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-19390-8_53A large quantity of documents used every day are still handwritten. However, it is interesting to transform each of these documents into its digital version for managing, archiving and sharing. Here we present Escritoire, a multi-touch desk that allows the user to capture, transcribe and work with handwritten documents. The desktop is continuously monitored using two cameras. Whenever the user makes a specific hand gesture over a paper, Escritoire proceeds to take an image. Then, the capture is automatically preprocesses, obtaining as a result an improved representation. Finally, the text image is transcribed using automatic techniques and finally the transcription is displayed on Escritoire.This work was partially supported by the Spanish MEC under FPU scholarship (AP2010-0575), STraDA research project (TIN2012-37475-C02-01) and MITTRAL research project (TIN2009-14633-C03-01); the EU’s 7th Framework Programme under tranScriptorium grant agreement (FP7/2007-2013/600707).Martín-Albo Simón, D.; Romero Gómez, V.; Vidal Ruiz, E. (2015). Escritoire: A Multi-touch Desk with e-Pen Input for Capture, Management and Multimodal Interactive Transcription of Handwritten Documents. En Pattern Recognition and Image Analysis. Springer. 471-478. https://doi.org/10.1007/978-3-319-19390-8_53S471478Andrew, A.: Another efficient algorithm for convex hulls in two dimensions. Inf. Process. Lett. 9(5), 216–219 (1979)Bosch, V., Toselli, A.H., Vidal, E.: Statistical text line analysis in handwritten documents. In: Proceedings of ICFHR (2012)Eisenstein, J., Puerta, A.: Adaptation in automated user-interface design. In: Proceedings of International Conference on Intelligent User Interfaces (2000)Jelinek, F.: Statistical Methods for Speech Recognition. MIT Press, Cambridge (1998)Kalman, R.E.: A new approach to linear filtering and prediction problems. Trans. ASME-J. Basic Eng. 82(Series D), 35–45 (1960)Keysers, D., Shafait, F., Breuel, T.M.: Document image zone classification - a simple high-performance approach. In: Proceedings of International Conference on Computer Vision Theory (2007)Kozielski, M., Forster, J., Ney, H.: Moment-based image normalization for handwritten text recognition. In: Proceedings of ICFHR (2012)Lampert, C.H., Braun, T., Ulges, A., Keysers, D., Breuel, T.M.: Oblivious document capture and real-time retrieval. In: International Workshop on Camera Based Document Analysis and Recognition (2005)Liang, J., Doermann, D., Li, H.: Camera based analysis of text and documents a survey. Int. J. Doc. Anal. Recogn. 7(2–3), 84–104 (2005)Liwicki, M., Rostanin, O., El-Neklawy, S.M., Dengel, A.: Touch & write: a multi-touch table with pen-input. In: Proceedings of International Workshop on Document Analysis Systems (2010)Marti, U.V., Bunke, H.: Text line segmentation and word recognition in a system for general writer independent handwriting recognition. In: Proceedings of ICDAR (2001)Martín-Albo, D., Romero, V., Toselli, A.H., Vidal, E.: Multimodal computer-assisted transcription of text images at character-level interaction. Int. J. Pattern Recogn. Artif. Intell. 26(5), 19 (2012)Martín-Albo, D., Romero, V., Vidal, E.: Interactive off-line handwritten text transcription using on-line handwritten text as feedback. In: Proceedings of ICDAR (2013)Mitra, S., Acharya, T.: Gesture recognition: a survey. IEEE Trans. Syst. Man Cybern. B Cybern. 37(3), 311–324 (2007)Terry, M., Mynatt, E.D.: Recognizing creative needs in user interface design. In: Proceedings of C&C (2002)Toselli, A.H., Juan, A., Keysers, D., González, J., Salvador, I., Ney, H., Vidal, E., Casacuberta, F.: Integrated handwriting recognition and interpretation using finite-state models. Int. J. Pattern Recognit. Artif. Intell. 18(4), 519–539 (2004)Toselli, A.H., Romero, V., Pastor, M., Vidal, E.: Multimodal interactive transcription of text images. Pattern Recognit. 43(5), 1814–1825 (2010)Toselli, A.H., Romero, V., Vidal, E.: Computer assisted transcription of text images and multimodal interaction. In: Popescu-Belis, A., Stiefelhagen, R. (eds.) MLMI 2008. LNCS, vol. 5237, pp. 296–308. Springer, Heidelberg (2008)Wachs, J.P., Kolsch, M., Stern, H., Edan, Y.: Vision-based hand-gesture applications. Commun. ACM. 54(2), 60–71 (2011)Wobbrock, J.O., Morris, M.R., Wilson, A.D.: User-defined gestures for surface computing. In: Proceedings of CHI (2009

Comparing the Cost Effectiveness of a Celiac Disease Panel to a Testing Cascade

Recent reductions in healthcare funding in the United States has pressured clinical laboratories to provide the same quality of diagnostic testing with fewer resources. Testing cascades have been developed to assist in the diagnosis of various illnesses, which use fewer tests and subsequently reduce costs. However, the cost effectiveness of a celiac disease (CD) testing cascade compared to a panel is currently unknown. Therefore, the purpose of this study was to determine if a CD testing cascade was equivalent to a panel in identifying patients deemed likely for CD, and to compare their cost effectiveness in a sample of symptomatic patients from Northeast Tennessee. A retrospective analysis using a CD testing cascade was performed on 933 outpatient samples referred to our laboratory from 2012 to 2017 with a request for a celiac disease serology panel. The seroprevalence of CD for the panel and the cascade were the same in this population (1.82%, 95% binomial confidence interval: 1.06% to 2.90%). The total cost of the CD cascade was 268% less than the cost of the panel resulting in a savings of $44,705, which translates to a savings of$47.92/patient. Based on these findings, we recommend utilization of the cascade to identify patients with likely CD. In the future, creative use of novel testing strategies can have significant contributions to healthcare reform and afford patients more cost-effective clinical diagnostic testing

Efficient filtering of adult content using textual information

Nowadays adult content represents a non negligible proportion of the Web content. It is of the utmost importance to protect children from this content. Search engines, as an entry point for Web navigation are ideally placed to deal with this issue. In this paper, we propose a method that builds a safe index i.e. adult-content free for search engines. This method is based on a filter that uses only textual information from the web page and the associated URL