Name
Abstract | ||
|---|---|---|
This paper presents an algorithm for estimating the local fractal dimension (LFD) of textured images. The algorithm is established by an experimental approach based on the blanket method. The proposed method uses the near optimum number of blankets to obtain the LFD for a small local window. The robustness of the proposed method to consistently estimate the LFD using up to a 3 × 3 local window is confirmed by experimental evaluations. The LFD maps, created from natural scenes, are utilized in an image segmentation algorithm that demonstrates the capability of rough segmentation of fine-texture regions in natural images. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1016/S0167-8655(02)00261-1 | Pattern Recognition Letters |
Keywords | Field | DocType |
blanket method,experimental evaluation,local image feature,experimental approach,image segmentation,lfd map,image segmentation algorithm,natural image,optimum estimation,local window,small local window,local fractal dimension,optimization,fractal dimension,consistent estimator,image features | Computer vision,Fractal dimension,Pattern recognition,Segmentation,Robustness (computer science),Image segmentation,Artificial intelligence,Image segmentation algorithm,Mathematics | Journal |
Volume | Issue | ISSN |
24 | 1-3 | Pattern Recognition Letters |
Citations | PageRank | References |
19 | 1.16 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sonny Novianto | 1 | 24 | 1.98 |
| Yukinori Suzuki | 2 | 68 | 8.71 |
| J. Maeda | 3 | 290 | 21.43 |