Name
Abstract | ||
|---|---|---|
Spiking neural P systems (namely SN P systems, for short) are bio-inspired neural-like computing models under the framework of membrane computing, which are also known as a new candidate of the third generation of neural networks. In this work, a parallel image skeletonizing method is proposed with SN P systems with weights. Specifically, an SN P system with weighs is constructed to achieve the Zhang–Suen image skeletonizing algorithm. Instead of serial calculation like Zhang–Suen image skeletonizing algorithm, the proposed method can parallel process a certain number of pixels of an image by spiking multiple neurons simultaneously at any computation step. Demonstrating via the experimental results, our method shows higher efficiency in data-reduction and simpler skeletons with less noise spurs than the method developed in Diazpernil (Neurocomputing 115:81–91, 2013) in skeletonizing images like hand-written words. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s11063-018-9947-9 | Neural Processing Letters |
Keywords | Field | DocType |
Membrane computing,Spiking neural P system,Image skeletonizing,Zhang–Suen algorithm | Pattern recognition,Parallel process,Skeletonization,Pixel,Artificial intelligence,Artificial neural network,Membrane computing,Mathematics,Computation,P system | Journal |
Volume | Issue | ISSN |
50 | 2 | 1573-773X |
Citations | PageRank | References |
4 | 0.47 | 30 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tao Song | 1 | 287 | 24.23 |
| Shanchen Pang | 2 | 50 | 14.19 |
| Shaohua Hao | 3 | 4 | 0.47 |
| Alfonso Rodríguez-Patón | 4 | 435 | 51.44 |
| pan zheng | 5 | 27 | 2.83 |