Name
Abstract | ||
|---|---|---|
This paper proposes a novel binary image thinning algorithm by using the autowaves generated by Pulse Coupled Neural Network (PCNN). Once the autowaves travelling in different directions meet, the PCNN delivers the thinning results. Four meeting conditions are given for autowaves meeting. If a neuron satisfies one of the four conditions, the pixel corresponding to this neuron belongs to the thinning result. Moreover, the specification of the PCNNs parameters is given, which makes the implementation of the proposed thinning algorithm easy. Experimental results show that the proposed algorithm is efficient in extracting the skeleton of images (such as Chinese characters, alphabet letters, numbers, fingerprints, etc.). Finally, a rate called "R MSkel" is given to evaluate the performance of different thinning algorithms, and comparisons show that the proposed algorithm has higher "R MSkel" and costs less time. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/s11063-006-9030-9 | Neural Processing Letters |
Keywords | Field | DocType |
Medial Axis Transformation,Pulse Coupled Neuron Network,Binary Images Thinning,Autowaves,Grassfire | Thinning,Pattern recognition,Autowave,Computer science,Binary image,Image processing,Algorithm,Fingerprint,Artificial intelligence,Pixel,Artificial neural network,Alphabet | Journal |
Volume | Issue | ISSN |
25 | 1 | 1370-4621 |
Citations | PageRank | References |
10 | 0.74 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lifeng Shang | 1 | 485 | 30.96 |
| Zhang Yi | 2 | 1765 | 194.41 |
| Luping Ji | 3 | 149 | 10.31 |