This paper proposes a new form document identification technique that uses the structure of cells in a form. The proposed method represents the cell structure by the location of the center points of each cell. This representation allows the form identification to be realized by a process of matching the points in an input image to the points in registered forms. We have implemented the point matching process using the two-dimensional hash table. This implementation enables the system to robustly identify an input form even if it is skewed or deformed by a scanning process, and to reduce the time for the identification. Moreover, the similarity between two forms defined by the implementation can be used to evaluate the identification ability when a set of registered forms is specified. Experimental results show the robustness and effectiveness of the proposed technique.

Article Free Access Share on A shot classification method of selecting effective key-frames for video browsing Authors: Hisashi Aoki Research and Development Center, Toshiba Corporation, 1, Komukai Toshiba-cho, Saiwai-ku, Kawasaki, Kanagawa 210, Japan Research and Development Center, Toshiba Corporation, 1, Komukai Toshiba-cho, Saiwai-ku, Kawasaki, Kanagawa 210, JapanView Profile , Shigeyoshi Shimotsuji Research and Development Center, Toshiba Corporation, 1, Komukai Toshiba-cho, Saiwai-ku, Kawasaki, Kanagawa 210, Japan Research and Development Center, Toshiba Corporation, 1, Komukai Toshiba-cho, Saiwai-ku, Kawasaki, Kanagawa 210, JapanView Profile , Osamu Hori Research and Development Center, Toshiba Corporation, 1, Komukai Toshiba-cho, Saiwai-ku, Kawasaki, Kanagawa 210, Japan Research and Development Center, Toshiba Corporation, 1, Komukai Toshiba-cho, Saiwai-ku, Kawasaki, Kanagawa 210, JapanView Profile Authors Info & Claims MULTIMEDIA '96: Proceedings of the fourth ACM international conference on MultimediaFebruary 1997 Pages 1–10https://doi.org/10.1145/244130.244135Published:01 February 1997Publication History 46citation744DownloadsMetricsTotal Citations46Total Downloads744Last 12 Months34Last 6 weeks4 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

The paper presents a new method for character string extraction that works efficiently even for a complicated geographical map. The concept of multi-scale measurement is introduced to achieve development of an efficient string detection technique. In this paper, scale means the size of the area where character candidates may exist. The proposed method first merges small black regions within a certain area into a mass. When the size of the area changes, the mass will change. The proposed method observes the change of a mass corresponding to the change of the size of the area, and searches for a stable mass as a character string. Multi-scale measurement enables the detection process to find the adequate size of an area to detect a string. Because a stable mass may include small figures, a test of the shape of a detected mass and a character recognition process follow to judge whether a mass forms a character string. If a mass is rejected, it is split into smaller masses according to the results of multi-scale measurement. These judgment and split processes are repeated to detect character strings from a pattern where several strings are written closely.

This paper presents a new precise line detection technique that works efficiently even for a complicated engineering drawing. Both the contours and skeletons of line regions in an image include crucial information for extracting lines precisely from a drawing. The usage of both contours and skeletons enables the following features: 1) the detected lines are hardly affected by intersecting or touching other lines; 2) the detected lines maintain the shape of the figures in the original drawing; and 3) the connectivity of lines in an image is preserved in the detected figures. Experiments on actually used drawings are discussed in order to evaluate the technique described.

This paper proposes an automatic interpretation method using probabilistic relaxation for line-drawings, which consist of lines, symbols, and characters, such as electricity distribution line diagrams superimposed on maps. An interpretation problem for lines is formulated as a labeling problem using probabilistic relaxation to obtain globally consistent results. The entire automatic interpretation consists of two stages. The first stage is segmentation and recognition for primitive components, like symbols, characters, and long lines. The second stage is long line interpretation, using probabilistic relaxation.>

A novel drawing recognition system which can be efficiently applied to degraded drawings with many line breaks, dimmed lines, and characters touching a line is proposed. The system is capable of both obtaining accurate line approximation and extracting the network structure of drawings. A three-layered intermediate description of a drawing image is employed for low-quality drawing recognition. A robust line extraction technique based on the contour curvature has been developed for this intermediate description. The proposed technique is designed for small-scale hardware implementation.>