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A robust and efficient algorithm for recognition of electrical symbols in digitized documents is proposed. The algorithm is based on morphological operations and geometric analysis to recognize different classes of symbols. Its novelty lies in building and usage of three spaces, namely H-, V -, and C-spaces, which respectively contain the horizontal line(More)
This paper presents a method to recognize and classify graphics in engineering drawing. The method consists of skeletonizing the input image, followed by segmentation of lines, arcs, and circles. Extracted line segments are classified into object lines, centerlines, dashed lines, and section lines, along with detection of arrowheads attached with lines and(More)
A novel integrated technique is proposed for hierarchical vectorization of electrical drawings in document images. Its first step includes recognition of different electrical symbols and their interconnections based on morphological operations and geometric analysis in three well-distinguished subspaces. This is followed by a hierarchical analysis for(More)
We propose here an efficient algorithm for high-level vectorization of scanned images of mechanical engineering drawings. The algorithm is marked by several novel features, which merit its superiority over the existing techniques. After preprocessing and necessary refinement of junction points in the image skeleton, it first extracts the graphic primitives,(More)
Though annotations are integral part of symbols in drawings, due attention is yet to be given for their identification, interpretation, and storage. A reconstructed drawing from the vector format is thus deficient in the complete description of the original, and hence requires costly and time-consuming manual intervention. This paper presents a method for(More)
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