Title :
An object-oriented progressive-simplification-based vectorization system for engineering drawings: model, algorithm, and performance
Author :
Song, Jiqiang ; Su, Feng ; Tai, Chiew-Lan ; Cai, Shijie
Author_Institution :
State Key Lab of Novel Software Technol., Nanjing Univ., China
fDate :
8/1/2002 12:00:00 AM
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 aground 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.
Keywords :
document image processing; engineering computing; object-oriented methods; engineering drawings; graphic object erasing; graphic object recognition; ground truth graphic object; object-oriented progressive-simplification-based vectorization system; raster image conversion; raw vector merger; raw vector search; raw vectors; recognition quality; two-phase workflow; vectorization; Character recognition; Degradation; Engineering drawings; Graphics; Humans; Image converters; Image recognition; Interference elimination; Merging; Object oriented modeling;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2002.1023802