Off-line Arabic Handwriting Recognition System Using Fast Wavelet Transform

In this research, off-line handwriting recognition system for Arabic alphabet is introduced. The system contains three main stages: preprocessing, segmentation and recognition stage. In the preprocessing stage, Radon transform was used in the design of algorithms for page, line and word skew correction as well as for word slant correction. In the segmentation stage, Hough transform approach was used for line extraction. For line to words and word to characters segmentation, a statistical method using mathematic representation of the lines and words binary image was used. Unlike most of current handwriting recognition system, our system simulates the human mechanism for image recognition, where images are encoded and saved in memory as groups according to their similarity to each other. Characters are decomposed into a coefficient vectors, using fast wavelet transform, then, vectors, that represent a character in different possible shapes, are saved as groups with one representative for each group. The recognition is achieved by comparing a vector of the character to be recognized with group representatives. Experiments showed that the proposed system is able to achieve the recognition task with 90.26% of accuracy. The system needs only 3.41 seconds a most to recognize a single character in a text of 15 lines where each line has 10 words on average

Contribution à l'analyse de la dynamique des écritures anciennes pour l'aide à l'expertise paléographique

Mes travaux de thèse s inscrivent dans le cadre du projet ANR GRAPHEM1 (Graphemebased Retrieval and Analysis for PaleograpHic Expertise of Middle Age Manuscripts). Ilsprésentent une contribution méthodologique applicable à l'analyse automatique des écrituresanciennes pour assister les experts en paléographie dans le délicat travail d étude et dedéchiffrage des écritures.L objectif principal est de contribuer à une instrumetation du corpus des manuscritsmédiévaux détenus par l Institut de Recherche en Histoire des Textes (IRHT Paris) en aidantles paléographes spécialisés dans ce domaine dans leur travail de compréhension de l évolutiondes formes de l écriture par la mise en place de méthodes efficaces d accès au contenu desmanuscrits reposant sur une analyse fine des formes décrites sous la formes de petits fragments(les graphèmes). Dans mes travaux de doctorats, j ai choisi d étudier la dynamique del élément le plus basique de l écriture appelé le ductus2 et qui d après les paléographes apportebeaucoup d informations sur le style d écriture et l époque d élaboration du manuscrit.Mes contributions majeures se situent à deux niveaux : une première étape de prétraitementdes images fortement dégradées assurant une décomposition optimale des formes en graphèmescontenant l information du ductus. Pour cette étape de décomposition des manuscrits, nousavons procédé à la mise en place d une méthodologie complète de suivi de traits à partir del extraction d un squelette obtenu à partir de procédures de rehaussement de contraste et dediffusion de gradients. Le suivi complet du tracé a été obtenu à partir de l application des règlesfondamentales d exécution des traits d écriture, enseignées aux copistes du Moyen Age. Il s agitd information de dynamique de formation des traits portant essentiellement sur des indicationsde directions privilégiées.Dans une seconde étape, nous avons cherché à caractériser ces graphèmes par desdescripteurs de formes visuelles compréhensibles à la fois par les paléographes et lesinformaticiens et garantissant une représentation la plus complète possible de l écriture d unpoint de vue géométrique et morphologique. A partir de cette caractérisation, nous avonsproposé une approche de clustering assurant un regroupement des graphèmes en classeshomogènes par l utilisation d un algorithme de classification non-supervisé basée sur lacoloration de graphe. Le résultat du clustering des graphèmes a conduit à la formation dedictionnaires de formes caractérisant de manière individuelle et discriminante chaque manuscrittraité. Nous avons également étudié la puissance discriminatoire de ces descripteurs afin d obtenir la meilleure représentation d un manuscrit en dictionnaire de formes. Cette étude a étéfaite en exploitant les algorithmes génétiques par leur capacité à produire de bonne sélection decaractéristiques.L ensemble de ces contributions a été testé à partir d une application CBIR sur trois bases demanuscrits dont deux médiévales (manuscrits de la base d Oxford et manuscrits de l IRHT, baseprincipale du projet), et une base comprenant de manuscrits contemporains utilisée lors de lacompétition d identification de scripteurs d ICDAR 2011. L exploitation de notre méthode dedescription et de classification a été faite sur une base contemporaine afin de positionner notrecontribution par rapport aux autres travaux relevant du domaine de l identification d écritures etétudier son pouvoir de généralisation à d autres types de documents. Les résultats trèsencourageants que nous avons obtenus sur les bases médiévales et la base contemporaine, ontmontré la robustesse de notre approche aux variations de formes et de styles et son caractèrerésolument généralisable à tout type de documents écrits.My thesis work is part of the ANR GRAPHEM Project (Grapheme based Retrieval andAnalysis for Expertise paleographic Manuscripts of Middle Age). It represents a methodologicalcontribution applicable to the automatic analysis of ancient writings to assist the experts inpaleography in the delicate work of the studying and deciphering the writing.The main objective is to contribute to an instrumentation of the corpus of medievalmanuscripts held by Institut de Recherche en Histoire de Textes (IRHT-Paris), by helping thepaleographers specialized in this field in their work of understanding the evolution of forms inthe writing, with the establishment of effective methods to access the contents of manuscriptsbased on a fine analysis of the forms described in the form of small fragments (graphemes). Inmy PhD work, I chose to study the dynamic of the most basic element of the writing called theductus and which according to the paleographers, brings a lot of information on the style ofwriting and the era of the elaboration of the manuscript.My major contribution is situated at two levels: a first step of preprocessing of severelydegraded images to ensure an optimal decomposition of the forms into graphemes containingthe ductus information. For this decomposition step of manuscripts, we have proceeded to theestablishment of a complete methodology for the tracings of strokes by the extraction of theskeleton obtained from the contrast enhancement and the diffusion of the gradient procedures.The complete tracking of the strokes was obtained from the application of fundamentalexecution rules of the strokes taught to the scribes of the Middle Ages. It is related to thedynamic information of the formation of strokes focusing essentially on indications of theprivileged directions.In a second step, we have tried to characterize the graphemes by visual shape descriptorsunderstandable by both the computer scientists and the paleographers and thus unsuring themost complete possible representation of the wrting from a geometrical and morphological pointof view. From this characterization, we have have proposed a clustering approach insuring agrouping of graphemes into homogeneous classes by using a non-supervised classificationalgorithm based on the graph coloring. The result of the clustering of graphemes led to theformation of a codebook characterizing in an individual and discriminating way each processedmanuscript. We have also studied the discriminating power of the descriptors in order to obtaina better representation of a manuscript into a codebook. This study was done by exploiting thegenetic algorithms by their ability to produce a good feature selection.The set of the contributions was tested from a CBIR application on three databases ofmanuscripts including two medieval databases (manuscripts from the Oxford and IRHTdatabases), and database of containing contemporary manuscripts used in the writersidentification contest of ICDAR 2011. The exploitation of our description and classificationmethod was applied on a cotemporary database in order to position our contribution withrespect to other relevant works in the writrings identification domain and study itsgeneralization power to other types of manuscripts. The very encouraging results that weobtained on the medieval and contemporary databases, showed the robustness of our approachto the variations of the shapes and styles and its resolutely generalized character to all types ofhandwritten documents.PARIS5-Bibliotheque electronique (751069902) / SudocSudocFranceF

Off-line Arabic Handwriting Recognition System Using Fast Wavelet Transform

In this research, off-line handwriting recognition system for Arabic alphabet is introduced. The system contains three main stages: preprocessing, segmentation and recognition stage. In the preprocessing stage, Radon transform was used in the design of algorithms for page, line and word skew correction as well as for word slant correction. In the segmentation stage, Hough transform approach was used for line extraction. For line to words and word to characters segmentation, a statistical method using mathematic representation of the lines and words binary image was used. Unlike most of current handwriting recognition system, our system simulates the human mechanism for image recognition, where images are encoded and saved in memory as groups according to their similarity to each other. Characters are decomposed into a coefficient vectors, using fast wavelet transform, then, vectors, that represent a character in different possible shapes, are saved as groups with one representative for each group. The recognition is achieved by comparing a vector of the character to be recognized with group representatives. Experiments showed that the proposed system is able to achieve the recognition task with 90.26% of accuracy. The system needs only 3.41 seconds a most to recognize a single character in a text of 15 lines where each line has 10 words on average

Using codebooks generated from text skeletonization for forensic writer identification

In this paper, we propose a novel approach for writer identification using codebook generation based on text skeletonization.Unlike other schemes, the skeleton in this approach is segmented at its junction pixels into elementary graphic units called graphemes. The codebook is generated by clustering the graphemes according to their distributions into a predefined grid. This method has been evaluated using the benchmarking dataset of the International Conference on Document Analysis and Recognition (ICDAR 2011) writer identification contest and has shown promising results. We also studied the effect of the amount of handwriting on the identification accuracy of the method and demonstrated that the proposed method is valid for Latin and Greek languages

Spotting Keywords in Offline Handwritten Documents Using Hausdorff Edit Distance

Keyword spotting has become a crucial topic in handwritten document recognition, by enabling content-based retrieval of scanned documents using search terms. With a query keyword, one can search and index the digitized handwriting which in turn facilitates understanding of manuscripts. Common automated techniques address the keyword spotting problem through statistical representations. Structural representations such as graphs apprehend the complex structure of handwriting. However, they are rarely used, particularly for keyword spotting techniques, due to high computational costs. The graph edit distance, a powerful and versatile method for matching any type of labeled graph, has exponential time complexity to calculate the similarities of graphs. Hence, the use of graph edit distance is constrained to small size graphs. The recently developed Hausdorff edit distance algorithm approximates the graph edit distance with quadratic time complexity by efficiently matching local substructures. This dissertation speculates using Hausdorff edit distance could be a promising alternative to other template-based keyword spotting approaches in term of computational time and accuracy. Accordingly, the core contribution of this thesis is investigation and development of a graph-based keyword spotting technique based on the Hausdorff edit distance algorithm. The high representational power of graphs combined with the efficiency of the Hausdorff edit distance for graph matching achieves remarkable speedup as well as accuracy. In a comprehensive experimental evaluation, we demonstrate the solid performance of the proposed graph-based method when compared with state of the art, both, concerning precision and speed. The second contribution of this thesis is a keyword spotting technique which incorporates dynamic time warping and Hausdorff edit distance approaches. The structural representation of graph-based approach combined with statistical geometric features representation compliments each other in order to provide a more accurate system. The proposed system has been extensively evaluated with four types of handwriting graphs and geometric features vectors on benchmark datasets. The experiments demonstrate a performance boost in which outperforms individual systems

Biometric Systems

Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study

Políticas de Copyright de Publicações Científicas em Repositórios Institucionais: O Caso do INESC TEC

A progressiva transformação das práticas científicas, impulsionada pelo desenvolvimento das novas Tecnologias de Informação e Comunicação (TIC), têm possibilitado aumentar o acesso à informação, caminhando gradualmente para uma abertura do ciclo de pesquisa. Isto permitirá resolver a longo prazo uma adversidade que se tem colocado aos investigadores, que passa pela existência de barreiras que limitam as condições de acesso, sejam estas geográficas ou financeiras. Apesar da produção científica ser dominada, maioritariamente, por grandes editoras comerciais, estando sujeita às regras por estas impostas, o Movimento do Acesso Aberto cuja primeira declaração pública, a Declaração de Budapeste (BOAI), é de 2002, vem propor alterações significativas que beneficiam os autores e os leitores. Este Movimento vem a ganhar importância em Portugal desde 2003, com a constituição do primeiro repositório institucional a nível nacional. Os repositórios institucionais surgiram como uma ferramenta de divulgação da produção científica de uma instituição, com o intuito de permitir abrir aos resultados da investigação, quer antes da publicação e do próprio processo de arbitragem (preprint), quer depois (postprint), e, consequentemente, aumentar a visibilidade do trabalho desenvolvido por um investigador e a respetiva instituição. O estudo apresentado, que passou por uma análise das políticas de copyright das publicações científicas mais relevantes do INESC TEC, permitiu não só perceber que as editoras adotam cada vez mais políticas que possibilitam o auto-arquivo das publicações em repositórios institucionais, como também que existe todo um trabalho de sensibilização a percorrer, não só para os investigadores, como para a instituição e toda a sociedade. A produção de um conjunto de recomendações, que passam pela implementação de uma política institucional que incentive o auto-arquivo das publicações desenvolvidas no âmbito institucional no repositório, serve como mote para uma maior valorização da produção científica do INESC TEC.The progressive transformation of scientific practices, driven by the development of new Information and Communication Technologies (ICT), which made it possible to increase access to information, gradually moving towards an opening of the research cycle. This opening makes it possible to resolve, in the long term, the adversity that has been placed on researchers, which involves the existence of barriers that limit access conditions, whether geographical or financial. Although large commercial publishers predominantly dominate scientific production and subject it to the rules imposed by them, the Open Access movement whose first public declaration, the Budapest Declaration (BOAI), was in 2002, proposes significant changes that benefit the authors and the readers. This Movement has gained importance in Portugal since 2003, with the constitution of the first institutional repository at the national level. Institutional repositories have emerged as a tool for disseminating the scientific production of an institution to open the results of the research, both before publication and the preprint process and postprint, increase the visibility of work done by an investigator and his or her institution. The present study, which underwent an analysis of the copyright policies of INESC TEC most relevant scientific publications, allowed not only to realize that publishers are increasingly adopting policies that make it possible to self-archive publications in institutional repositories, all the work of raising awareness, not only for researchers but also for the institution and the whole society. The production of a set of recommendations, which go through the implementation of an institutional policy that encourages the self-archiving of the publications developed in the institutional scope in the repository, serves as a motto for a greater appreciation of the scientific production of INESC TEC