Name
Abstract | ||
|---|---|---|
This paper proposes a novel thinning algorithm and applies it to automatic constrained ZIP code segmentation. The segmentation method consists of two main stages: removal of rectangle boxes and location of ZIP code digits. Both the two stages are implemented on the skeleton of boxes, which is extracted by the proposed pulse coupled neural network (PCNN) based thinning algorithm. This algorithm is specially designed to merely skeletonize the boxes. At the second stage, a projection method is employed to segment ZIP code image into its constituent digits. Experimental results show that the proposed method is very efficient in segmenting ZIP code images even with noise. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.neucom.2008.07.010 | Neurocomputing |
Keywords | Field | DocType |
segmentation method,zip code digit,proposed pulse,zip code segmentation,constituent digit,constrained zip code segmentation pulse coupled neural network skeleton projection,pulse coupled neural network,zip code image,projection,segment zip code image,projection method,constrained zip code segmentation,skeleton | Pattern recognition,Segmentation,Computer science,Rectangle,Projection method,Artificial intelligence,Artificial neural network,Machine learning,Thinning algorithm | Journal |
Volume | Issue | ISSN |
72 | 7-9 | Neurocomputing |
Citations | PageRank | References |
2 | 0.41 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lifeng Shang | 1 | 485 | 30.96 |
| Zhang Yi | 2 | 1765 | 194.41 |
| Luping Ji | 3 | 149 | 10.31 |