基于SVM的自然图像显著性建筑检测

Qu Yanyun, Zheng Nanning, Li Cuihua, Yuan Zejian
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引用次数: 3

摘要

本文提出了一种基于支持向量机的显著性建筑物的高度特征检测算法。对图像进行两级Haar小波分解,增强候选建筑。然后将需要的区域从背景中分离出来。提出了一套结构特征集,利用Sobel算子捕捉突出建筑的一般统计特性。该方法已在许多实际实例上进行了测试,取得了良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Salient building detection in natural image using SVM
This paper present a novel algorithm via support vector machine to detect the salient buildings whose height and many features make them stand out. Two-level Haar wavelet decomposition is implemented on the image to enhance the building candidates. And then the desired regions are separated from the background. A set of structure features is proposed to capture the generic statistic properties of the salient building using Sobel operator. The proposed approach has been tested on many real examples with good results.
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