Kernel fitting for image segmentation
| Autor: | Ben-Yong Liu, Wen-Yue Wu, Xiao-Wei Chen |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
business.industry
Segmentation-based object categorization ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-space segmentation Pattern recognition Image segmentation Thresholding Kernel method Kernel (image processing) Computer Science::Computer Vision and Pattern Recognition Histogram Curve fitting Artificial intelligence business Mathematics |
| Zdroj: | 2008 International Conference on Machine Learning and Cybernetics. |
| DOI: | 10.1109/icmlc.2008.4620906 |
| Popis: | Previously, a classifier called Kernel-based Nonlinear Representor (KNR) was proposed for pattern classification. In this paper KNR is changed to curve fitting for image segmentation applications. For each gray level, a curve is estimated by KNR and separated from that of a higher gray level by a threshold obtained from Newman-Pearson criterion. The thresholds are then merged into a few representative ones, with an ideal high-pass filtering approach, for image segmentation. Feasibility of the presented method in image segmentation is illustrated by some experimental results. |
| Databáze: | OpenAIRE |
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