Juan F. Arias

Detection of Horizontal Lines in Noisy Run Length Encoded Images: The FAST Method

We present a fast method for finding horizontal lines in run length encoded images. The method was motivated by the need for quick and reliable detection of horizontal lines in an interactive drawing conversion system for telephone company drawings. At the core of the algorithm are the processes of filtering run lengths, assembling filtered run lengths, generating top silhouette, and thresholding the gradient of the top silhouette to extract one horizontal line at a time. The method is robust in the presence of distortion; it can tolerate significant skew and warping, both local and global, and can bridge significant breaks in lines without too many false positive lines.

Interpretation of telephone system manhole drawings

Abstract We present methodologies for interpreting manhole drawings of a telephone company for information extraction. A graphics interpretation system was developed to extract the information about cables and interconnections inside the manhole and present it in a format suitable for a CAD-based system. Experimental results are shown.

Interpreting and representing tabular documents

This paper describes a methodology to interpret the information from telephone company DSX assignment table drawings. Horizontal lines are found using an efficient algorithm that works over the run-length encoded representation of the image. For vertical lines, the image is transposed using an efficient method we developed, and the algorithm for horizontal lines is applied again. Using the information about the lines, the tabular structures are extracted by finding biconnected components on the graph formed by the lines and their intersections. A methodology has also been developed for the representation of end access to the entries inside the tables.

Efficient techniques for telephone company line drawing interpretation

In this paper we present the idea of using customizable tools to develop systems to interpret telephone company drawings. These drawings are composed primarily of horizontal and vertical lines. By selecting the intersections as primitives, routines are developed to establish spatial relations of the primitives which are used to describe the structures. Another aspect that as presented is the benefit of using run length encoding to reduce the amount of memory and the processing time needed to process the large files resulting from scanning the forementioned drawings. Examples of the interpretation of telephone company distributing frame and front equipment drawings are presented.

Efficient extraction of primitives from line drawings composed of horizontal and vertical lines

Abstract. The performance of the algorithms for the extraction of primitives for the interpretation of line drawings is usually affected by the degradation of the information contained in the document due to factors such as low print contrast, defocusing, skew, etc. In this paper, we are proposing two algorithms for the extraction of primitives with good performance under degradation. The application of the algorithms is restricted to line drawings composed of horizontal and vertical lines. The performance of the algorithms has been evaluated by using a protocol described in the literature.

A Practical Application of Graphics Recognition: Helping with the Extraction of Information from Telephone Company Drawings

This paper presents an application of graphics recognition technology to tackle specific problems to help in the extraction of information from telephone company drawings. Our approach is contrary to the view of creating graphics recognition systems that can handle different types of problems and perform automated conversion. In this paper we present an example where a small system was constructed to help in the extraction of title information to correct the information in an existing drawings database.

A memory efficient method for fast transposing run-length encoded images

We present a memory efficient method for transposing a run-length encoded bi-level image. Image transposing is a commonly used operation for affine transformations such as document image deskewing. The best existing method for transposing a run-length image is the pxy table based method. For images of typical engineering drawings, which are large, crowded and noisy, this method requires an exorbitant amount of memory. The method proposed uses a very compact representation of run-length encoded images. Also, it bypasses certain steps from the pxy table based method. Consequently, the saving in memory use is proportional to the number of horizontal runs and the number of vertical (transposed) runs. The computation time for both the methods is almost identical.

Finding straight lines in drawings

We have developed an efficient method to extract straight lines at any orientation from a line drawing. The method works by extracting the horizontal and vertical lines using the FAST method, detecting the angles of the other lines and applying the FAST method again while the image is rotated to each corresponding angle. The method is efficient because it is based on very efficient line finding, transposition, and rotation operations which work over the run-length representation of the line drawing.

Efficient interpretation of tabular documents

We present efficient techniques for the interpretation and representation of tabular documents. Our goal is to achieve processing times that are fast enough for an interactive table conversion system. The techniques are based on the run-length encoded representation of scanned documents. We use DSX assignment tables, a predominant type of engineering drawing in telephone company central offices, as sample images in this paper. However, the techniques presented can be applied directly to tabular documents in any application.

Interpretation of telephone company central office equipment drawings

This paper describes a methodology to interpret central office drawings using basic features in order to increase the efficiency of the interpretation. To interpret these drawings, the intersections between vertical and horizontal lines are located and related to obtain the position of boxes. Once the graphical information is interpreted, a grammar driven intelligent character recognition (ICR) system is used to extract text information in order to complete the interpretation of the drawing.