Texture segmentation using multiscale Hurst features

被引：0
|
作者：
Kaplan, LM
Murenzi, R
机构：
来源：
INTERNATIONAL CONFERENCE ON IMAGE PROCESSING - PROCEEDINGS, VOL III | 1997年
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D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we evaluate the effectiveness of multiscale Hurst parameters as features for texture segmentation. These extended Hurst features quantize texture roughness at various scales. The performance of these new features are compared against standard Hurst features using images of texture mosaics. For the experiments, the performance was evaluated with and without supplemental contrast and average grayscale features.
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页码：205 / 208
页数：4
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