Name
Abstract | ||
|---|---|---|
In order to obtain homogeneous regions and smooth contours for region-oriented image compression, gradient-coupled spiking cortex model is designed and applied to digital image segmentation. Inspired by the knowledge of visual cortex, the model is composed of neurons with spike coupling and gradient enhancement, and it is same as the one in the visual cortex which can distinguish some objects in real scene through capturing boundary information. The model smoothes pixels within regions and enhances pixels at boundaries by creating a fitting function. Outputs of the model are the desired segmented image after connection components label. Experiments show that the method not only detects regions of original image, but also remains succinct effective contours, so it is suitable for region-oriented image compression. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.neucom.2012.01.007 | Neurocomputing |
Keywords | Field | DocType |
connection components label,gradient-coupled spiking cortex model,boundary information,region-oriented image compression,detects region,segmented image,digital image segmentation,model smoothes pixel,region segmentation method,original image,visual cortex,segmentation,neural network,image processing | Scale-space segmentation,Feature detection (computer vision),Computer science,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Minimum spanning tree-based segmentation,Computer vision,Pattern recognition,Image texture,Range segmentation,Machine learning,Image compression | Journal |
Volume | ISSN | Citations |
85, | 0925-2312 | 3 |
PageRank | References | Authors |
0.46 | 20 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rongchang Zhao | 1 | 30 | 4.63 |
| Yide Ma | 2 | 459 | 34.74 |