A Hough transform based line recognition method utilizing both parameter space and image space
✍ Scribed by Jiqiang Song; Michael R. Lyu
- Publisher
- Elsevier Science
- Year
- 2005
- Tongue
- English
- Weight
- 652 KB
- Volume
- 38
- Category
- Article
- ISSN
- 0031-3203
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✦ Synopsis
Hough Transform (HT) is recognized as a powerful tool for graphic element extraction from images due to its global vision and robustness in noisy or degraded environment. However, the application of HT has been limited to small-size images for a long time. Besides the well-known heavy computation in the accumulation, the peak detection and the line verification become much more time-consuming for large-size images. Another limitation is that most existing HT-based line recognition methods are not able to detect line thickness, which is essential to large-size images, usually engineering drawings. We believe these limitations arise from that these methods only work on the HT parameter space. This paper therefore proposes a new HTbased line recognition method, which utilizes both the HT parameter space and the image space. The proposed method devises an image-based gradient prediction to accelerate the accumulation, introduces a boundary recorder to eliminate redundant analyses in the line verification, and develops an image-based line verification algorithm to detect line thickness and reduce false detections as well. It also proposes to use pixel removal to avoid overlapping lines instead of rigidly suppressing the N × N neighborhood. We perform experiments on real images with different sizes in terms of speed and detection accuracy. The experimental results demonstrate the significant performance improvement, especially for large-size images.