Cellular neural networks with opposite-sign templates for image thinning
✍ Scribed by Wang, Jun-Sheng; Gan, Qiang; Wei, Yu; Xie, Li
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 131 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0098-9886
No coin nor oath required. For personal study only.
✦ Synopsis
This paper presents image thinning algorithms using cellular neural networks (CNNs) with one-or two-dimensional opposite-sign templates (OSTs) as well as non-unity gain output functions. Two four-layer CNN systems with one-dimensional (1-D) OSTs are proposed for image thinning with 4-or 8-connectivity, respectively. A CNN system, which consists of an eight-layer CNN with two-dimensional (2-D) OSTs followed by another four-layer CNN with 2-D OSTs, is constructed for image thinning with 8-connectivity, in which designs of B-and I-templates are simpler than in CNNs with 1-D OSTs. In the aforementioned designs, parameter values of 1-D OSTs are chosen to make CNNs operate with thinning-like property 1 (TL-1), and those of 2-D OSTs with 2-D thinning-like property (2-DTL). Simulation studies show that these CNN systems have a good image thinning performance.