A New Approach for Line Recognition in Large-size Images Using Hough Transform

The application of Hough Transform (HT) has been limited to small-size images for a long time. For large-size images, the peak detection and the line verification become much more time-consuming. Many HT-based line detection methods are not able to detect line width. This paper proposes a new approach for detecting line segments using HT, which makes HT applicable to largesize images, especially for those applications whose line width is critical. Our approach applies a boundary recorder to eliminate redundant analyses, and employs an image-analysis-based line-verification method to overcome the difficulty of using a threshold to distinguish short lines from noise. It avoids the overlapping lines by removing the pixels of detected line segments, which is more robust than only clearing the N×N neighborhood. This approach could be easily extended to improved HT methods that perform the global accumulation. The experimental result shows that this approach is very timeefficient for large-size images.