Masakazu Suzuki

Bio: Masakazu Suzuki is an academic researcher from Kyushu University. The author has contributed to research in topics: Optical character recognition & Reading (process). The author has an hindex of 14, co-authored 57 publications receiving 805 citations.

INFTY: an integrated OCR system for mathematical documents

Abstract: An integrated OCR system for mathematical documents, called INFTY, is presented. INFTY consists of four procedures, i.e., layout analysis, character recognition, structure analysis of mathematical expressions, and manual error correction. In those procedures, several novel techniques are utilized for better recognition performance. Experimental results on about 500 pages of mathematical documents showed high character recognition rates on both mathematical expressions and ordinary texts, and sufficient performance on the structure analysis of the mathematical expressions.

Mathematical formula recognition using virtual link network

Abstract: We propose a new method of recognizing mathematical formulae. The method is robust against the recognition errors of characters and the variation of the printing styles of the documents. The outline is as follows: we first construct a network with vertices representing the characters (symbols), linked with each other by several edges with labels and costs representing the possible relations of the pair of characters. The network has multiple edges with different labels and costs representing the ambiguity of the decision of the relation of character pairs. Then, we output the spanning tree of the network with minimum cost which corresponds to the recognition result of the structure of the mathematical formula, using not only the local costs initially attached to the network but the costs reflecting global structure of the formula. The advantage of this method is that local errors of the recognition are recovered automatically by the total cost of the recognition tree.

A ground-truthed mathematical character and symbol image database

Abstract: This paper describes the specifications for our ground-truthed mathematical character and symbol image database, called InftyCDB-1. The ground-truth of each character is composed of type, font, quality (touched/broken) and link (relative position), etc. The database includes all the characters and symbols of 467 pages of 30 articles on mathematics, and is organized so that it can be used as word image database or as mathematical formula image database. InftyCDB-1 is a public database that is freely usable for research and development purposes.

An Integrated OCR Software for Mathematical Documents and Its Output with Accessibility

Abstract: This paper describes shortly a practical integrated system for scientific documents including mathematical formulae, named ‘Infty’ The system consists of three components of applications: an OCR system named ‘InftyReader’, an editor named ‘InftyEditor’ and converting tools into various formats Those applications are linked each other via XML files

Recognition and retrieval of mathematical expressions

Abstract: Document recognition and retrieval technologies complement one another, providing improved access to increasingly large document collections. While recognition and retrieval of textual information is fairly mature, with wide-spread availability of optical character recognition and text-based search engines, recognition and retrieval of graphics such as images, figures, tables, diagrams, and mathematical expressions are in comparatively early stages of research. This paper surveys the state of the art in recognition and retrieval of mathematical expressions, organized around four key problems in math retrieval (query construction, normalization, indexing, and relevance feedback), and four key problems in math recognition (detecting expressions, detecting and classifying symbols, analyzing symbol layout, and constructing a representation of meaning). Of special interest is the machine learning problem of jointly optimizing the component algorithms in a math recognition system, and developing effective indexing, retrieval and relevance feedback algorithms for math retrieval. Another important open problem is developing user interfaces that seamlessly integrate recognition and retrieval. Activity in these important research areas is increasing, in part because math notation provides an excellent domain for studying problems common to many document and graphics recognition and retrieval applications, and also because mature applications will likely provide substantial benefits for education, research, and mathematical literacy.

Recognizing mathematical expressions using tree transformation

Abstract: We describe a robust and efficient system for recognizing typeset and handwritten mathematical notation. From a list of symbols with bounding boxes the system analyzes an expression in three successive passes. The Layout Pass constructs a Baseline Structure Tree (BST) describing the two-dimensional arrangement of input symbols. Reading order and operator dominance are used to allow efficient recognition of symbol layout even when symbols deviate greatly from their ideal positions. Next, the Lexical Pass produces a Lexed BST from the initial BST by grouping tokens comprised of multiple input symbols; these include decimal numbers, function names, and symbols comprised of nonoverlapping primitives such as "=". The Lexical Pass also labels vertical structures such as fractions and accents. The Lexed BST is translated into L/sup A/T/sub E/X. Additional processing, necessary for producing output for symbolic algebra systems, is carried out in the Expression Analysis Pass. The Lexed BST is translated into an Operator Tree, which describes the order and scope of operations in the input expression. The tree manipulations used in each pass are represented compactly using tree transformations. The compiler-like architecture of the system allows robust handling of unexpected input, increases the scalability of the system, and provides the groundwork for handling dialects of mathematical notation.

INFTY: an integrated OCR system for mathematical documents

Abstract: An integrated OCR system for mathematical documents, called INFTY, is presented. INFTY consists of four procedures, i.e., layout analysis, character recognition, structure analysis of mathematical expressions, and manual error correction. In those procedures, several novel techniques are utilized for better recognition performance. Experimental results on about 500 pages of mathematical documents showed high character recognition rates on both mathematical expressions and ordinary texts, and sufficient performance on the structure analysis of the mathematical expressions.

Automating tactile graphics translation

Abstract: Access to graphical images (bar charts, diagrams, line graphs, etc.) that are in a tactile form (representation through which content can be accessed by touch) is inadequate for students who are blind and take mathematics, science, and engineering courses. We describe our analysis of the current work practices of tactile graphics specialists who create tactile forms of graphical images. We propose automated means by which to improve the efficiency of current work practices.We describe the implementation of various components of this new automated process, which includes image classification, segmentation, simplification, and layout. We summarize our development of the tactile graphics assistant, which will enable tactile graphics specialists to be more efficient in creating tactile graphics both in batches and individually. We describe our unique team of researchers, practitioners, and student consultants who are blind, all of whom are needed to successfully develop this new way of translating tactile graphics.