Εκπαίδευση - Σπουδές

  • Δίπλωμα, Τμήμα Ηλεκτρολόγων Μηχανικών και Τεχνολογίας Υπολογιστών, Πανεπιστήμιο Πατρών (1996).
  • Διδακτορικό, Τμήμα Ηλεκτρολόγων Μηχανικών και Τεχνολογίας Υπολογιστών, Πανεπιστήμιο Πατρών (2000).
  • Πτυχίο, Ισπανική Γλώσσα και Πολιτισμός, ΕΑΠ, (2007).

Ερευνητικά Ενδιαφέροντα

  • Επεξεργασία Εικόνας
  • Τεχνητή Όραση
  • Επεξεργασια Εικόνων Εγγράφων
  • Ρομποτική

Διδασκαλία

  • Επεξεργασία Εικόνας και Ρομποτική Όραση (Μεταπτυχιακό)
  • Ερευνητική/Αναπτυξιακή Εργασία (Μεταπτυχιακό)
  • Μεθοδολογίες και Γλώσσες Προγραμματισμού Ι (C++)
  • Αναγνώριση Προτύπων & Εφαρμογές στη Ρομποτική (7ο εξάμηνο)
  • Τεχνητή Όραση (9ο Εξάμηνο)

Επιτροπές - Διοικητικό έργο

  • Ομάδα Εσωτερικής Αξιολόγησης Τμήματος
  • Επιτροπή Κατατακτηρίων Εξετάσεων

Δημοσιεύσεις σε Διεθνή Περιοδικά (Journals)


Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.


Radib Kar, Souvik Saha, Suman Kumar Bera, E. Kavallieratou, Vikrant Bhateja, Ram Sarkar, Novel approaches towards slope and slant correction for tri-script handwritten word images, The Imaging Science Journal, Vol. 67, No. 3, pp. 159-170, 2019, Taylor & Francis,
 

Abstract
Slope and slant correction of offline handwritten word images are two of the major pre-processing steps in document image processing, because these reduce the variations in writing, thereby make further processing of the same much easier. This paper presents novel slope and slant correction methods that are applied in three different script handwritten words namely Devanagari, Bangla and Roman. The language dependency and the computational complexity of state-of-the-art approaches towards the word level slope and slant correction are addressed here. A new technique for approximate core region detection is introduced here for skew detection and then linear regression is recursively applied to de-skew the word image. Whereas, in case of slant correction, a novel cost function over the vertical projection of de-skewed image is designed and optimized to fix the uniform slant angle of text words. A new …

Sourav Ghosh, Dibyadwati Lahiri, Showmik Bhowmik, E. Kavallieratou, Ram Sarkar, Text/non-text separation from handwritten document images using LBP based features: An empirical study, Journal of Imaging, Vol. 4, No. 4, pp. 57, 2018, Multidisciplinary Digital Publishing Institute,
 

Abstract
Isolating non-text components from the text components present in handwritten document images is an important but less explored research area. Addressing this issue, in this paper, we have presented an empirical study on the applicability of various Local Binary Pattern (LBP) based texture features for this problem. This paper also proposes a minor modification in one of the variants of the LBP operator to achieve better performance in the text/non-text classification problem. The feature descriptors are then evaluated on a database, made up of images from 104 handwritten laboratory copies and class notes of various engineering and science branches, using five well-known classifiers. Classification results reflect the effectiveness of LBP-based feature descriptors in text/non-text separation.

K. Karampidis, E. Kavallieratou, G. Papadourakis, A review of image steganalysis techniques for digital forensics, Journal of information security and applications, Vol. 40, pp. 217-235, 2018, Elsevier,
 

Abstract
Steganalysis and steganography are the two different sides of the same coin. Steganography tries to hide messages in plain sight while steganalysis tries to detect their existence or even more to retrieve the embedded data. Both steganography and steganalysis received a great deal of attention, especially from law enforcement. While cryptography in many countries is being outlawed or limited, cyber criminals or even terrorists are extensively using steganography to avoid being arrested with encrypted incriminating material in their possession. Therefore, understanding the ways that messages can be embedded in a digital medium –in most cases in digital images-, and knowledge of state of the art methods to detect hidden information, is essential in exposing criminal activity. Digital image steganography is growing in use and application. Many powerful and robust methods of steganography and steganalysis …

E. Kavallieratou, L Likforman-Sulem, N. Vasilopoulos, Slant Removal Technique for Historical Document Images, Journal of Imaging, Vol. 4, No. 6, pp. 80, 2018, Multidisciplinary Digital Publishing Institute,
 

Abstract
Slanted text has been demonstrated to be a salient feature of handwriting. Its estimation is a necessary preprocessing task in many document image processing systems in order to improve the required training. This paper describes and evaluates a new technique for removing the slant from historical document pages that avoids the segmentation procedure into text lines and words. The proposed technique first relies on slant angle detection from an accurate selection of fragments. Then, a slant removal technique is applied. However, the presented slant removal technique may be combined with any other slant detection algorithm. Experimental results are provided for four document image databases: two historical document databases, the TrigraphSlant database (the only database dedicated to slant removal), and a printed database in order to check the precision of the proposed technique.

L Likforman-Sulem, E. Kavallieratou, Document Image Processing, Journal of Imaging, Vol. 4, No. 7, pp. 84, 2018, Multidisciplinary Digital Publishing Institute,
 

Abstract
The Special Issue “Document Image Processing” in the Journal of Imaging aims at presenting approaches which contribute to access the content of document images. These approaches are related to low level tasks such as image preprocessing, skew/slant corrections, binarization and document segmentation, as well as high level tasks such as OCR, handwriting recognition, word spotting or script identification. This special issue brings together 12 papers that discuss such approaches. The first three articles deal with historical document preprocessing. The work by Hanif et al.[1] aims at removing bleed-through using a non-linear model, and at reconstructing the background by an inpainting approach based on non-local patch similarity. The paper by Almeida et al.[2] proposes a new binarization approach that includes a decision-based process for finding the best threshold for each RGB channel. In the paper by Kavallieratou et al.[3], a segmentation-free approach based on the Wigner-Ville distribution is used to detect the slant of a document and correct it. Once a document image is preprocessed, a next step described in the paper by Ghosh et al.[4] consists in separating text components from non-text ones, using a classifier based on LBP features. Following steps may consist in recognizing text components or searching from word queries. In the paper by Nashwan et al.[5] a holistic-based approach for the recognition of printed Arabic words is proposed, coupled with an efficient dictionary reduction. In the work by Nagendar et al.[6] it is shown that using a query specific fast Dynamic Time Warping distance, improves the Direct Query Classifier …

Manolis Koubarakis, Konstantinos Blekas, Anastasia Krithara, George Vouros, Georgios Chalkiadakis, Vassilis Plagianakos, Christos Tjortjis, E. Kavallieratou, Dimitris Vrakas, Nikolaos Mavridis, AI in Greece: The Case of Research on Linked Geospatial Data, AI Magazine, Vol. 39, No. 2, pp. 91-96, 2018, Association for the Advancement of Artificial Intelligence,
 

Abstract
We survey the AI research carried out in Greece recently. We concentrate on the case of linked geospatial data, an area with significant practical importance, very interesting research results, and implemented systems developed by a Greek research team.

N. Vasilopoulos, E. Kavallieratou, Unified layout analysis and text localization framework, Journal of Electronic Imaging, Vol. 26, No. 1, pp. 013009, 2017, International Society for Optics and Photonics,
 

Abstract
A technique appropriate for extracting textual information from documents with complex layouts, such as newspapers and journals, is presented. It is a combination of a foreground analysis and a text localization method. The first one is used to segment the page in text and nontext blocks, whereas the second one is used to detect text that may be embedded inside images, charts, diagrams, tables, etc. Detailed experiments on two public databases showed that mixing layout analysis and text localization techniques can lead to improved page segmentation and text extraction results.

K. Karampidis, E. Kavallieratou, G. Papadourakis, Comparison of Classification Algorithms for File Type Detection A Digital Forensics Perspective, Polibits, Vol. 56, pp. 15-20, 2017,
 

Abstract
Computer Science and it focuses on the acquisition, preservation and analysis of digital evidence, in a way that that these evidences are suitable for presentation in a court of law. Forensic investigators follow a standard set of procedures. One major and difficult problem is the correct identification of file types. Criminals often hide evidence in a digital device, by changing the file type. It is very common, a child predator to try to hide image files with immoral content in order to fool police authorities. In this paper we examine a methodology for file type identification, which uses computational intelligence techniques for feature selection and classification. This methodology was applied to the three most common image file types (jpg, png and gif). In order to ascertain the method’s accuracy, different machine learning classifiers were utilized. A three stage process involving feature extraction (Byte Frequency Distribution), feature selection (genetic algorithm) and classification (decision tree, support vector machine, neural network, logistic regression and k-nearest neighbor) was examined. Experiments were conducted having files altered in a digital forensics perspective and the results are presented. The examined methodology showed-in most casesvery high and exceptional accuracy in file type identification.

N. Vasilopoulos, E. Kavallieratou, Complex layout analysis based on contour classification and morphological operations, Engineering Applications of Artificial Intelligence, Vol. 65, pp. 220-229, 2017, Pergamon,
 

Abstract
In this paper, a hybrid technique for complex layout analysis is presented. Morphological operations are applied to both the foreground and the background, in order to connect neighboring regions and detect separator lines and columns respectively. Contour tracing is used for the extraction of shape and size information and classification of the connected components. Evaluated on the RDCL-2015 dataset, the method achieved state-of-art results in less than three seconds per page.

P. Diamantatos, E. Kavallieratou, S. Gritzalis, Skeleton Hinge Distribution for Writer Identification, International Journal on Artificial Intelligence Tools, Vol. 25, No. 3, pp. 1-14, 2016, Springer, http://www.worldscientific.com/worl..., indexed in SCI-E, IF = 0.778
 

Abstract
In this paper, a feature that is based on statistical directional features is presented. Specifically, an improvement of the statistical feature: edge hinge distribution, is attempted. Furthermore, different matching techniques are applied. For the evaluation, the Firemaker DB was used, which consists of samples from 250 writers, including 4 pages per writer. The suggested feature, the skeleton hinge distribution, achieved accuracy of 90.8% using nearest neighbor with Manhattan distance for matching.

[11]
E. Kavallieratou, F.Daskas, Text Line Detection and Segmentation: Uneven Skew Angles and Hill-and-Dale Writing, Journal of Universal Computer Science, Vol. 17, No. 1, pp. 16-29, 2011, http://www.jucs.org/jucs_17_1/text_...
[12]
K.Zagoris, E. Kavallieratou, N. Papamarkos, Image retrieval systems based on compact shape descriptor and relevance feedback information, Journal of Visual Communication and Image Representation, 2011
[13]
K.Zagoris, E. Kavallieratou, N. Papamarkos, Document Image Retrieval System, Engineering Applications of Artificial Intelligence, Vol. 23, No. 6, pp. 872-879, 2010, Elsevier,
[14]
P. Stathis, E. Kavallieratou, N. Papamarkos, An Evaluation Technique for Binarization Algorithms, Journal of Universal Computer Science (J.UCS), Vol. 14, No. 18, pp. 3011 - 3030, 2009,
[15]
E. Kavallieratou, N. Dromazou, N. Fakotakis, G. Kokkinakis, An Integrated System for Handwritten Document Image Processing, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 17, No. 4, pp. 101-120, 2003,
[16]
E. Kavallieratou, N. Fakotakis, G. Kokkinakis, Skew Angle Estimation for Printed and Handwritten Documents using the Wigner-Ville Distribution, Image & Vision Computing, Vol. 20, No. 11, pp. 813-822, 2002,
[17]
E. Kavallieratou, N. Fakotakis, G. Kokkinakis, Un Off-line Unconstrained Handwritting Recognition System, International Journal of Document Analysis and Recognition, No. 4, pp. 226-242, 2002,
[18]
E. Kavallieratou, N. Fakotakis, G. Kokkinakis, Slant Estimation Algorithm for OCR Systems, Pattern Recognition, Vol. 34, No. 12, pp. 2515-2522, 2001,
[19]
E. Kavallieratou, N. Fakotakis, G. Kokkinakis, A slant removal algorithm, Pattern Recognition, Vol. 33, pp. 1261-1262, 2000,
[20]
E. Kavallieratou, N. Fakotakis, G. Kokkinakis, Skew Estimation using Cohen’s class distributions, Pattern Recognition Letters, Vol. 20, pp. 1305-1311, 1999,

Επιστημονικά Συνέδρια (Conferences)


Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.


E. Kavallieratou, Carlos R del-Blanco, Carlos Cuevas, Narciso García, Interactive learning-based retrieval technique for visual lifelogging, International Conference of the Cross-Language Evaluation Forum for European Languages, Springer, Cham, pp. 226-237, Dec, 2019,
 

Abstract
Currently, there is a plethora of video wearable devices that can easily collect data from daily user life. This fact has promoted the development of lifelogging applications for security, healthcare, and leisure. However, the retrieval of not-pre-defined events is still a challenge due to the impossibility of having a potentially unlimited number of fully annotated databases covering all possible events. This work proposes an interactive and weakly supervised learning approach that is able of retrieving any kinds of events using general and weakly annotated databases. The proposed system has been evaluated with the database provided by the Lifelog Moment Retrieval (LMRT) challenge of ImageCLEF (Lifelog2018), where it reached the first position in the final ranking.

Bogdan Ionescu, Henning Müller, Renaud Péteri, Yashin Dicente Cid, Vitali Liauchuk, Vassili Kovalev, Dzmitri Klimuk, Aleh Tarasau, Asma Ben Abacha, E. Kavallieratou, ImageCLEF 2019: Multimedia retrieval in medicine, lifelogging, security and nature, International Conference of the Cross-Language Evaluation Forum for European Languages, pp. 358-386, Dec, 2019, Springer, Cham,
 

Abstract
This paper presents an overview of the ImageCLEF 2019 lab, organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2019. ImageCLEF is an ongoing evaluation initiative (started in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2019, the 17th edition of ImageCLEF runs four main tasks: (i) a medical task that groups three previous tasks (caption analysis, tuberculosis prediction, and medical visual question answering) with new data, (ii) a lifelog task (videos, images and other sources) about daily activities understanding, retrieval and summarization, (iii) a new security task addressing the problems of automatically identifying forged content and retrieve hidden information, and (iv) a new coral task about …

Bogdan Ionescu, Henning Müller, Renaud Péteri, Duc-Tien Dang-Nguyen, Luca Piras, Michael Riegler, Minh-Triet Tran, Mathias Lux, Cathal Gurrin, E. Kavallieratou, ImageCLEF 2019: Multimedia Retrieval in Lifelogging, Medical, Nature, and Security Applications, European Conference on Information Retrieval, Springer, Cham, pp. 301-308, Dec, 2019,
 

Abstract
This paper presents an overview of the foreseen ImageCLEF 2019 lab that will be organized as part of the Conference and Labs of the Evaluation Forum - CLEF Labs 2019. ImageCLEF is an ongoing evaluation initiative (started in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2019, the 17th edition of ImageCLEF will run four main tasks: (i) a Lifelog task (videos, images and other sources) about daily activities understanding, retrieval and summarization, (ii) a Medical task that groups three previous tasks (caption analysis, tuberculosis prediction, and medical visual question answering) with newer data, (iii) a new Coral task about segmenting and labeling collections of coral images for 3D modeling, and (iv) a new Security task …

E. Kavallieratou, Carlos R del-Blanco, Carlos Cuevas, Narciso García, Retrieving Events in Life Logging, CLEF (Working Notes), Dec, 2018,
 

Abstract
This paper describes our contribution for the Lifelog Moment Retrieval (LMRT) challenge of ImageCLEF Lifelog2018. Lifelogging has a tremendous potential in many applications. However, the wide range of possible moment events along with the lack of fully annotated databases make this task very challenging. This work proposes an interactive and weakly supervised learning approach that can dramatically reduce the time to retrieve any kind of events in huge databases. Impressive results have been obtained in the referred challenge, reaching the first rank.

N. Vasilopoulos, Yazan Wasfi, E. Kavallieratou, Automatic Text Extraction from Arabic Newspapers, International Conference Image Analysis and Recognition, Springer, Cham, pp. 505-510, Dec, 2018,
 

Abstract
A system for extracting the textual information from document images with complex layouts is presented. It is based on both layout analysis and text localization techniques. Layout analysis is first applied to segment the page in text and non-text blocks and then text localization is used to detect text that may be embedded inside images, charts, diagrams, tables etc. Detailed experiments on scanned Arabic newspapers showed that combining layout analysis and text localization methods can lead to improved page segmentation and text extraction results.

Ioanna Bakali, D. Chatzis, Nikolaos Mavropoulos, Nikolaos Fourtounis, Maria Soulountsi, Nikolaos Manos, Aristotelis Theodoulidis, Panagiotis Papanastasiou, E. Kavallieratou, Control a robot via internet using a block programming platform for educational purposes, Proceedings of the 10th Hellenic Conference on Artificial Intelligence, ACM, pp. 59, Dec, 2018,
 

Abstract
This paper deals with a system consisting of a robot named El Greco that can be programmed via internet and livestreaming from any place, anywhere, to move on a play room as well as perform other functions such as to produce voice in many languages, recognize voice commands, recognize faces, perceive its environment, perform combined movements and provide information by searching the Internet. All these capabilities of the robot can be programmed using a friendly block programming platform that has been developed to be used by students for educational purposes. The system was used by a number of students and the results of two questionnaires before and after the use are reported.

Pavlos Skoupras, Maria Soulountsi, Shubham Khandelwal, Jaideep Upadhyay, Konstantinos Paraskevas, Georgios Zervas, Nikolaos Fourtounis, Dimitris Katsios, Giorgos Papamichalakis, E. Kavallieratou, El Greco: a 3d-printed humanoid that anybody can afford, Proceedings of the 10th Hellenic Conference on Artificial Intelligence, ACM, pp. 58, Dec, 2018,
 

Abstract
In this paper, the humanoid robot named El Greco is presented (design, hardware and software). The humanoids from DARPA Robotics Challenge inspired us in many aspects, while at the same time the goal was to maintain a low cost and build a humanoid accordingly, so that we can create a model that is affordable and easy to build in order to be used by the youth. The entire assembly of the robot consists of parts such as limbs, head, body, legs and the base which are 3D printed. All the details over the design specifications and the problems incurred during the development of the humanoid are described under each module of the humanoid. Further details and results are given over the open source software of El Greco.

Ankit Kumar Sah, Showmik Bhowmik, Samir Malakar, Ram Sarkar, E. Kavallieratou, N. Vasilopoulos, Text and non-text recognition using modified HOG descriptor, 2017 IEEE Calcutta Conference (CALCON), IEEE, pp. 64-68, Dec, 2017,
 

Abstract
In order to convert a document image in its editable version, an OCR engine must identify and separate the nontext regions from text regions of a given document image. In the present work, a technique is developed to classify various text and non-text regions present in a document image. For that purpose, a modified version of Histogram of Oriented Gradient (HOG) is used as a feature descriptor. Multi-Layer Perceptron (MLP) is chosen from a pool of classifier by comparing the recognition accuracy of it with two other well-known classifiers viz., Random Forest (RF), Nave Bayes (NB). The designed technique is evaluated on a dataset, containing 862 images of manually extracted regions from two standard databases namely, RDCL2015 dataset and Media Team Document dataset. The proposed system has achieved 96.44% recognition accuracy and outperformed some of the state-of-the-art feature descriptors …

P. Diamantatos, E. Kavallieratou, S. Gritzalis, Writer Identification using Statistical and Model Based Approach, ICFHR 2014 14th International Conference on Frontiers in Handwriting Recognition, J. Llados, R. Manmatha, C. - L. Tan, (eds), pp. 589-594, Sep, 2014, Crete, Greece, ICFHR , http://www.icfhr2014.org/
 

Abstract
The state-of-the-art writer identification systems use a variety of different features and techniques in order to identify the writer of the handwritten text. In this paper several statistical and model based features are presented. Specifically, an improvement of a statistical feature, the edge hinge distribution, is attempted. Furthermore, the combination of this feature with a model-based feature is explored, that is based on a codebook of graphemes. For the evaluation, the Firemaker DB was used, which consists of 250 writers, including 4 pages per writer. The best result for the statistical suggested approach, the skeleton hinge distribution, achieved accuracy of 90,8%, while the combination of this method with the codebook of graphemes reached 96%.

P. Diamantatos, E. Kavallieratou, P Gomez-Gil, Binarization: a Tool for Text Localization, ICFHR 2014 14th International Conference on Frontiers in Handwriting Recognition, J. Llados, R. Manmatha, C. - L. Tan, (eds), Sep, 2014, Crete, Greece, ICFHR, http://www.icfhr2014.org/
 

Abstract
This paper presents a novel procedure for localizing text on scene photos. It takes advantage of the fact that text should present some contrast in comparison with the background, in order to be distinguished by the human eye. A procedure of binarization is applied in order to create appropriate images for the text detection. The connected components of the image are extracted and some heuristic rules are applied in order to identify areas containing text. Finally, the overlaps are handled and the false detections are rejected. The method is evaluated using images of natural scene taken from the robust reading competition of ICDAR2011. The results are promising and some useful conclusions are drawn.

P. Diamantatos, E. Kavallieratou, Android Based Electronic Travel Aid System for Blind People, AIAI 2014 Artificial Intelligence Applications and Innovations, pp. 585-592, Sep, 2014, Rhodes, Greece, Springer Berlin Heidelberg, http://delab.csd.auth.gr/aiai2014/
 

Abstract
Blindness is the condition of lacking visual perception due to physiological or neurological factors. Blind people do not have the full perception of the surrounding environment, though navigating, in an unknown environment or/and with obstacles on route, can be a very difficult task. In this paper, an information mobile system is presented, that acts as an electronic travel aid, and can guide a blind person through a route, inform him about imminent obstacles in his path and help him orientate himself. The current prototype consists of a mobile phone, and the developed application.

[12]
P.Diamantatos, V.Verras, E. Kavallieratou, Detecting Main Body Size in Document Images, Document Analysis and Recognition (ICDAR), 2013 12th International Conference on. IEEE, 2013., Dec, 2013,
[13]
P. Diamantatos, V.Verras, E. Kavallieratou, Detecting Main Body Size in Document Images., ICDAR, pp. 1160-1164, Dec, 2013,
K. Prokopiou, E. Kavallieratou, E. Stamatatos, An Image Processing Self-training System for Ruling Line Removal Algorithms, 18th Int. Conf. on Digital Signal Processing (DSP), Dec, 2013, IEEE,
 

Abstract
Ruling line removal is an important pre-processing step in document image processing. Several algorithms have been proposed for this task. However, it is important to be able to take full advantage of the existing algorithms by adapting them to the specific properties of a document image collection. In this paper, a system is presented, appropriate for fine-tuning the parameters of ruling line removal algorithms or appropriately adapt them to a specific document image collection, in order to improve the results. The application of our method to an existed line removal algorithms is presented.

[15]
N.Vasilopoulos, E. Kavallieratou, A classification-free word-spotting system, IS&T/SPIE Electronic Imaging. International Society for Optics and Photonics, Dec, 2013,
[16]
E.Matthaiou, E. Kavallieratou, An information extraction system from patient historical documents, Proceedings of the 27th Annual ACM Symposium on Applied Computing, , pp. 787-791, Dec, 2012,
[17]
E. Kavallieratou, D. Lopresti, C. Chen, Ruling line detection and removal, Proceedings of SPIE 7874, 78740V, Dec, 2011,
[18]
S.Vavilis, E. Kavallieratou, A tool for tuning binarization techniques, International Conference on Document Analysis and Recognition (ICDAR), Dec, 2011,
[19]
C. Chen, D. Lopresti, E. Kavallieratou, The Impact of Ruling Lines on Writer Identification, 2010 International Conference Frontiers in Handwriting Recognition (ICFHR), , Dec, 2010,
[20]
R Paredes, E. Kavallieratou, RD Lins, ICFHR 2010 contest: Quantitative evaluation of binarization algorithms, 2010 International Conference Frontiers in Handwriting Recognition (ICFHR), , Dec, 2010,
[21]
D. Lopresti, E. Kavallieratou, Ruling Line Removal in Handwritten Page Images, IEEE Proc. of 20th International Conference of Pattern Recognition (ICPR 2010), pp. 2704-2707, Dec, 2010,
[22]
E. Kavallieratou, Text line detection and segmentation: uneven skew angles and hill-and-dale writing, In Proceedings of the 2010 ACM Symposium on Applied Computing (Sierre, Switzerland, March 22 - 26, 2010). SAC '10. ACM, New York, NY, pp. 59-60, Dec, 2010,
J.Margaronis, M.Christou, E. Kavallieratou, Theodoros Tzouramanis, GCDB: a character database system, In Proceedings of the international Workshop on Multilingual OCR (Barcelona, Spain, July 25 - 25, 2009). ICDAE , Dec, 2009, ACM Press, http://tinyurl.com/okhxrpj,
 

Abstract
In this article the GCDB (Greek Characters DataBase) System is presented. GCDB is a complete database system for storing images of Greek unconstrained handwritten characters. The three elements that compose this database are: a specialized input form, a database that contains the images of the filled forms and the software that allows the inputting of the data from the form into the database and their retrieval. The main purpose of this database system is to make it possible to achieve the automatic storage and organization of images of Greek symbols and letters in view of their use by OCR (Optical Character Recognition) systems or other applications. The GCDB system is designed within the concept of future expansion, providing an up to date database of Greek handwritten characters to cover the growing demands for offline character recognition of the Greek language.

[24]
N. Doulgeri, E. Kavallieratou, Retrieval of Historical Documents by Word Spotting, IS&T/SPIE Electronic Imaging 2009, Dec, 2009,
[25]
K.Zagoris, E. Kavallieratou, N. Papamarkos, Developing Document Image Retrieval System, Proc. Of IADIS International Conference Computer Graphics and Visualization 2008, , pp. 119-126., Dec, 2008,
[26]
P. Stathis, E. Kavallieratou, N. Papamarkos, An Evaluation Survey of Binarization Algorithms on Historical Documents, IEEE 19th International Conference on Pattern Recognition (ICPR'08), Dec, 2008,
[27]
E. Kavallieratou, An objective way to evaluate and compare binarization algorithms, 23rd Annual ACM Symposium on Applied Computing, Dec, 2008,
E. Kavallieratou, E. Stamatatos, Adaptive Binarization of Historical Document Images, 18th Int. Conf. on Pattern Recognition, pp. 742-745, Dec, 2006,
 

Abstract
In this paper, we present a binarization technique specifically designed for historical document images. Existing methods for this problem focus on either finding a good global threshold or adapting the threshold for each area so that to remove smear, strains, uneven illumination etc. We propose a hybrid approach that first applies a global thresholding method and, then, identifies the image areas that are more likely to still contain noise. Each of these areas is re-processed separately to achieve better quality of binarization. We evaluate the proposed approach for different kinds of degradation problems. The results show that our method can handle hard cases while documents already in good condition are not affected drastically.

E. Kavallieratou, E. Stamatatos, Improving the Quality of Degraded Document Images, 2nd IEEE Int. Conf. on Document Image Analysis for Libraries (DIAL), pp. 340-349, Dec, 2006,
 

Abstract
It is common for libraries to provide public access to historical and ancient document image collections. It is common for such document images to require specialized processing in order to remove background noise and become more legible. In this paper, we propose a hybrid binarizatin approach for improving the quality of old documents using a combination of global and local thresholding. First, a global thresholding technique specifically designed for old document images is applied to the entire image. Then, the image areas that still contain background noise are detected and the same technique is re-applied to each area separately. Hence, we achieve better adaptability of the algorithm in cases where various kinds of noise coexist in different areas of the same image while avoiding the computational and time cost of applying a local thresholding in the entire image. Evaluation results based on a collection of historical document images indicate that the proposed approach is effective in removing background noise and improving the quality of degraded documents while documents already in good condition are not affected.

[30]
E. Kavallieratou, H. Antonopoulou, Cleaning and Enhancing Historical Document Images, Advanced Concepts for Intelligent Vision Systems, pp. 681-688, Dec, 2005, Springer-Verlag,
[31]
E. Kavallieratou, A Binarization Algorithm specialized on Document Images and Photos, 8th International Conference of Document Analysis and Recognition (ICDAR 2005), pp. 463-467, Dec, 2005, Seoul,
E. Stamatatos, E. Kavallieratou, Music Performer Verification Based on Learning Ensembles, Methods and Applications of Artificial Intelligence, G. Vouros, (ed), pp. 122 – 131, Dec, 2004,
 

Abstract
In this paper the problem of music performer verification is introduced. Given a certain performance of a musical piece and a set of candidate pianists the task is to examine whether or not a particular pianist is the actual performer. A database of 22 pianists playing pieces by F. Chopin in a computercontrolled piano is used in the presented experiments. An appropriate set of features that captures the idiosyncrasies of music performers is proposed. Wellknown machine learning techniques for constructing learning ensembles are applied and remarkable results are described in verifying the actual pianist, a very difficult task even for human experts.

E. Kavallieratou, E. Stamatatos, Discrimination of Machine-Printed from Handwritten Text Using Simple Structural Characteristics, 17th International Conference on Pattern Recognition (ICPR 2004), Dec, 2004,
 

Abstract
In this paper, we present a trainable approach to discriminate between machine-printed and handwritten text. An integrated system able to localize text areas and split them in text-lines is used. A set of simple and easyto- compute structural characteristics that capture the differences between machine-printed and handwritten text-lines is introduced. Experiments on document images taken from IAM-DB and GRUHD databases show a remarkable performance of the proposed approach that requires minimal training data.

[34]
E. Kavallieratou, S. Stamatatos, H. Antonopoulou, Machine-Printed from Handwritten Text Discrimination, 9th Int’l Workshop on Frontiers in Handwriting Recognition (IWFHR-9), pp. 312-316, Dec, 2004,
[35]
E. Kavallieratou, K. Sgarbas, N. Fakotakis, G. Kokkinakis, Handwritten Word Recognition based on Structural Characteristics and Lexical Support, ICDAR 2003, pp. 562-566, Aug, 2003, Edinburgh, Scotland,
[36]
M. Maragoudakis, E. Kavallieratou, N. Fakotakis, G. Kokkinakis, An Effective Stochastic Estimation of Handwritten Character Segmentation Bounds, ISAP 2003: Competitive Environment, Renewable Energy, Distributed Generation, Aug, 2003, Lemnos, Greece,
[37]
M. Maragoudakis, E. Kavallieratou, N. Fakotakis, Improving handwritten character segmentation by incorporating Bayesian knowledge with support vector machines, IEEE Int. Conf. Audio Speech & Signal Processing ICASSP2002, Dec, 2002, Orlando-Florida,
[38]
M. Maragoudakis, E. Kavallieratou, N. Fakotakis, Incorporating Conditional Independence Assumption with Support Vector Machines to enhance Handwritten Character Segmentation Performance, 16th International Conference of the International Association of Pattern Recognition ICPR 2002, pp. 911-914, Dec, 2002, Quebec-Canada,
[39]
N. Liolios, E. Kavallieratou, N. Fakotakis, G. Kokkinakis, A New Shape Transformation Approach to Handwritten Character Recognition, 16th International Conference of the International Association of Pattern Recognition ICPR 2002, pp. 584-587, Dec, 2002, Quebec-Canada,
[40]
E. Kavallieratou, N. Fakotakis, G. Kokkinakis, Handwritten Character Recognition based on Structural Characteristics, 16th International Conference of the International Association of Pattern Recognition ICPR 2002, pp. 139-142, Dec, 2002, Quebec-Canada,
[41]
S. Moeller, E. Kavallieratou, Diagnostic Assessment of Telephone Transmission Impact on ASR Performance and Human-to-Human Speech Quality, 3rd Int. Conf. on Language Resources and Evaluation (LREC 2002), pp. 1177-1184, Dec, 2002, ES-Las Palmas,
[42]
M. Maragoudakis, E. Kavallieratou, N. Fakotakis, G. Kokkinakis, How Conditional Independence Assumption Affects Handwritten Character Segmentation, IAPR, ICDAR’2001, 6th International Conference on Document Analysis and Recognition, pp. 246-250, Sep, 2001, Seattle, Washington, U.S.A,
[43]
E. Kavallieratou, N. Liolios, E. Koutsogeorgos, N. Fakotakis, G. Kokkinakis, The GRUHD database of Modern Greek Unconstrained Handwriting, ICDAR’2001, pp. 561-565, Dec, 2001,
[44]
E. Kavallieratou, D. C. Balcan, M. F. Popa, N. Fakotakis, Handwritten Text Localization in Skewed Documents, ICIP’2001, pp. 1102-1105, Dec, 2001,
[45]
E. Kavallieratou, N. Liolios, E. Koutsogeorgos, N. Fakotakis, G. Kokkinakis, The GRUHD database of Modern Greek Unconstrained Handwriting, LREC 2000, pp. 1755-1759, Dec, 2000,
E. Kavallieratou, E. Stamatatos, N. Fakotakis, G. Kokkinakis, Handwritten Character Segmentation Using Transformation-Based Learning, 15th Int. Conf. on Pattern Recognition (ICPR2000), pp. 634-637, Dec, 2000,
 

Abstract
This paper presents a character segmentation algorithm for unconstrained cursive handwritten text. The transformation-based learning method and a simplified variation of it are used in order to extract automatically rules that detect the segment boundaries. Comparative experimental results are given for a collection of multi-writer handwritten words. The achieved accuracy in detecting segment boundaries exceeds 82%. Moreover, limited training data can provide very satisfactory results.

[47]
E. Kavallieratou, N. Fakotakis, G. Kokkinakis, New algorithms for skewing correction and slant removal on word-level, ICECS’99, pp. 1159-1162, Dec, 1999,
[48]
E. Kavallieratou, N. Antoniadis, N. Fakotakis, G. Kokkinakis, Extraction and Recognition of Handwritten Alphanumeric Characters from Application forms, DSP97, pp. 695-698, Dec, 1997,

Βιβλία


Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.


[1]
E. Kavallieratou, L Likforman-Sulem, Document Image Processing, 2018, MDPI

Κεφάλαια σε Βιβλία


Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.


[1]
Venkatesan Rajinikanth, Nilanjan Dey, E. Kavallieratou, Hong Lin, Firefly Algorithm-Based Kapur’s Thresholding and Hough Transform to Extract Leukocyte Section from Hematological Images, chapter in: Applications of Firefly Algorithm and its Variants, Springer, Singapore, pp. , 2020,
[2]
S.Vavilis, E. Kavallieratou, R Paredes, K Sotiropoulos, A Hybrid Binarization Technique for Document Images, chapter in: Learning Structure and Schemas from Documents, pp. 165-179, 2011,

Επιμέλεια Πρακτικών Διεθνών Συνεδρίων


Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.