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Journal ArticleDOI

A system for interpretation of line drawings

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TLDR
An algorithm has been developed to locate and separate text strings of various font sizes, styles, and orientations by applying the Hough transform to the centroids of connected components in the image.
Abstract
A system for interpretation of images of paper-based line drawings is described. Since a typical drawing contains both text strings and graphics, an algorithm has been developed to locate and separate text strings of various font sizes, styles, and orientations. This is accomplished by applying the Hough transform to the centroids of connected components in the image. The graphics in the segmented image are processed to represent thin entities by their core-lines and thick objects by their boundaries. The core-lines and boundaries are segmented into straight line segments and curved lines. The line segments and their interconnections are analyzed to locate minimum redundancy loops which are adequate to generate a succinct description of the graphics. Such a description includes the location and attributes of simple polygonal shapes, circles, and interconnecting lines, and a description of the spatial relationships and occlusions among them. Hatching and filling patterns are also identified. The performance of the system is evaluated using several test images, and the results are presented. The superiority of these algorithms in generating meaningful interpretations of graphics, compared to conventional data compression schemes, is clear from these results. >

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Citations
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Journal ArticleDOI

Twenty years of document image analysis in PAMI

TL;DR: The contributions to document image analysis of 99 papers published in the IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) are clustered, summarized, interpolated, interpreted, and evaluated.
Journal ArticleDOI

Robust and accurate vectorization of line drawings

TL;DR: The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result.
Book ChapterDOI

Symbol Recognition: Current Advances and Perspectives

TL;DR: Issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work.
Journal ArticleDOI

Sparse pixel vectorization: an algorithm and its performance evaluation

TL;DR: This work presents a thinningless sparse pixel vectorization (SPV) algorithm, which is both time efficient and accurate, as evaluated by the proposed performance evaluation criteria.
References
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Journal ArticleDOI

On the detection of dominant points on digital curves

TL;DR: A parallel algorithm for detecting dominant points on a digital closed curve is presented, which leads to the observation that the performance of dominant points detection depends not only on the accuracy of the measure of significance, but also on the precise determination of the region of support.
Journal ArticleDOI

A robust algorithm for text string separation from mixed text/graphics images

TL;DR: The development and implementation of an algorithm for automated text string separation that is relatively independent of changes in text font style and size and of string orientation are described and showed superior performance compared to other techniques.
Journal ArticleDOI

Adaptive smoothing: a general tool for early vision

TL;DR: Different implementations of adaptive smoothing are presented, first on a serial machine, for which a multigrid algorithm is proposed to speed up the smoothing effect, then on a single instruction multiple data (SIMD) parallel machine such as the Connection Machine.
Journal ArticleDOI

Block segmentation and text extraction in mixed text/image documents

TL;DR: It is shown that a constrained run length algorithm is well suited to partition most documents into areas of text lines, solid black lines, and rectangular ☐es enclosing graphics and halftone images.
Journal ArticleDOI

Analysis of textual images using the Hough transform

TL;DR: Methods for handling several discretization problems that arise in mapping the rectangular image space to the (ρ, Θ) accumulator array are described.
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