1 Thisbookcontainsrefereedandimprovedpaperspresentedatthe5thIAPR - ternational Workshop on Graphics Recognition (GREC 2003). GREC 2003 was held in the Computer Vision Center, in Barcelona (Spain) during July 30–31, 2003. TheGRECworkshopisthemainactivityoftheIAPR-TC10,theTechnical 2 Committee on Graphics Recognition . Edited volumes from the previous wo- shops in the series are available as Lecture Notes in Computer Science: LNCS Volume 1072 (GREC 1995 at Penn State University, USA), LNCS Volume 1389 (GREC 1997 in Nancy, France), LNCS Volume 1941 (GREC 1999 in Jaipur, India), and LNCS Volume 2390 (GREC 2001 in Kingston, Canada). Graphics recognition is a particular ?eld in the domain of document ana- sis that combines pattern recognition and image processing techniques for the analysis of any kind of graphical information in documents, either from paper or electronic formats. Topics of interest for the graphics recognition community are: vectorization; symbol recognition; analysis of graphic documents with - agrammatic notation like electrical diagrams, architectural plans, engineering drawings, musical scores, maps, etc. ; graphics-based information retrieval; p- formance evaluation in graphics recognition; and systems for graphics recog- tion. Inadditiontotheclassicobjectives,inrecentyearsgraphicsrecognitionhas faced up to new and promising perspectives, some of them in conjunction with other, a?ne scienti?c communities. Examples of that are sketchy interfaces and on-line graphics recognition in the framework of human computer interaction, or query by graphic content for retrieval and browsing in large-format graphic d- uments, digital libraries and Web applications. Thus, the combination of classic challenges with new research interests gives the graphics recognition ?eld an active scienti?c community, with a promising future.

This book contains refereed and improved papers presented at the Seventh IAPR Workshop on Graphics Recognition (GREC2007), held in Curitiba, Brazil, September 20-21, 2007. The GREC workshops provide an excellent opportunity for researchers and practitioners at all levels of experience to meet colleagues and to share new ideas and knowledge about graphics recognition methods. Graphics recognition is a subfield of document image analysis that deals with graphical entities in engineering drawings, sketches, maps, architectural plans, musical scores, mathematical notation, tables, diagrams, etc. GREC2007 continued the tradition of past workshops held at Penn State University, USA (GREC 1995, LNCS Volume 1072, Springer, 1996); Nancy, France (GREC 1997, LNCS Volume 1389, Springer, 1998); Jaipur, India (GREC 1999, LNCS Volume 1941, Springer, 2000); Kingston, Canada (GREC 2001, LNCS Volume 2390, Springer, 2002); Barcelona, Spain (GREC 2003, LNCS Volume 3088, Springer, 2004); and Hong Kong, China (GREC 2005, LNCS Volume 3926, Springer, 2006). GREC2007 was also the first edition of a GREC workshop held at the same location of the ICDAR conference and it facilitated people to attend to both events. The program of GREC2007 was organized in a single-track 2-day workshop. It comprised several sessions dedicated to specific topics.

This book constitutes the thoroughly refereed post-proceedings of the 6th International Workshop on Graphics Recognition, GREC 2005, held in Hong Kong, China, August 2005. The book presents 37 revised full papers together with a panel discussion report, organized in topical sections on engineering drawings vectorization and recognition, symbol recognition, graphic image analysis, structural document analysis, sketching and online graphics recognition, curves and shape processing, and graphics recognition contest results.

The book focuses on one of the key issues in document image processing – graphical symbol recognition, which is a sub-field of the larger research domain of pattern recognition. It covers several approaches: statistical, structural and syntactic, and discusses their merits and demerits considering the context. Through comprehensive experiments, it also explores whether these approaches can be combined. The book presents research problems, state-of-the-art methods that convey basic steps as well as prominent techniques, evaluation metrics and protocols, and research standpoints/directions that are associated with it. However, it is not limited to straightforward isolated graphics (visual patterns) recognition; it also addresses complex and composite graphical symbols recognition, which is motivated by real-world industrial problems.

This book presents refereed and revised papers presented at GREC 2001, the 4th IAPR International Workshop on Graphics Recognition, which took place in Kingston, Ontario, Canada in September 2001. Graphics recognition is a branch of document image analysis that focuses on the recognition of two-dimensional notations such as engineering drawings, maps, mathematical notation, music notation, tables, and chemical structure diagrams. Due to the growing demand for both o?-line and on-line document recognition systems, the ?eld of graphics recognition has an excitingand promisingfuture. The GREC workshops provide an opportunity for researchers at all levels of experience to share insights into graphics recognition methods. The workshops enjoy strongparticipation from researchers in both industry and academia. They are sponsored by IAPR TC-10, the Technical Committee on Graphics Recog- tion within the International Association for Pattern Recognition. Edited v- umes from the previous three workshops in this series are available as Lecture Notes in Computer Science, Vols. 1072, 1389, and 1941. After the GREC 2001 workshop, authors were invited to submit enhanced versions of their papers for review. Every paper was evaluated by three reviewers. We are grateful to both authors and reviewers for their careful work during this review process. Many of the papers that appear in this volume were thoroughly revised and improved, in response to reviewers’ suggestions.

This book brings all the major and frontier topics in the field of document analysis together into a single volume, creating a unique reference source that will be invaluable to a large audience of researchers, lecturers and students working in this field. With chapters written by some of the most distinguished researchers active in this field, this book addresses recent advances in digital document processing research and development.

The Mexican International Conference on Artificial Intelligence (MICAI), a yearly international conference series organized by the Mexican Society for Artificial Intel- gence (SMIA), is a major international AI forum and the main event in the academic life of the country’s growing AI community. In 2008 Mexico celebrates the 50th an- versary of development of computer science in the country: in 1958 the first computer was installed at the National Autonomous University of Mexico (UNAM). Nowadays, computer science is the country’s fastest growing research area. The proceedings of the previous MICAI events were published by Springer in its Lecture Notes in Artificial Intelligence (LNAI) series, vol. 1793, 2313, 2972, 3789, 4293, and 4827. Since its foundation in 2000, the conference has been growing in popularity, and improving in quality. This volume contains the papers presented at the oral session of the 7th Mexican International Conference on Artificial Intelligence, MICAI 2008, held October 27–31, 2008, in Atizapán de Zaragoza, Mexico. The conference received for evaluation 363 submissions by 1,032 authors from 43 countries (see Tables 1 and 2). This volume contains revised versions of 94 papers by 308 authors from 28 countries selected - cording to the results of an international reviewing process. Thus the acceptance rate was 25.9%. The book is structured into 20 thematic fields representative of the main current areas of interest for the AI community, plus a section of invited papers: