An Object-Oriented Progressive-Simplification-Based Vectorization System for Engineering Drawings: Model, Algorithm, and Performance
Author(s): Jiqiang Song, Feng Su, Chiew-Lan Tai, Shijie Cai.
Article: IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 24, No. 8, pp. 1048--1060, August,
2002.
[BibTeX] 
Abstract:
Existing vectorization systems for engineering drawings usually take a two-phase workflow: convert a raster image to raw vectors and recognize graphic objects from the raw vectors. The first phase usually separates a ground truth graphic object that intersects
or touches other graphic objects into several parts, thus, the second phase faces the difficulty of searching for and merging raw vectors belonging to the same object. These operations slow down vectorization and degrade the recognition quality. Imitating the way humans
read engineering drawings, we propose an efficient one-phase object-oriented vectorization model that recognizes each class of graphic
objects from their natural characteristics. Each ground truth graphic object is recognized directly in its entirety at the pixel level. The raster
image is progressively simplified by erasing recognized graphic objects to eliminate their interference with subsequent recognition. To
evaluate the performance of the proposed model, we present experimental results on real-life drawings and quantitative analysis using
third party protocols. The evaluation results show significant improvement in speed and recognition rate.