摘要
基于场景全局语义特征描述符gist的自然场景分类方法在特征提取过程中计算量较大、识别精度较低。为此,提出一种改进的特征提取方法,将3尺度的gist特征与梯度方向直方图特征相结合对场景进行描述,并利用支持向量机实现分类。实验结果表明,改进的方法加快了特征提取速度,提高了分类正确率。
Feature extraction method for natural scene has some shortcomings such as large computing costs and low identification accuracy.So this paper proposes an improved extraction method.It combines three-scale gist feature with Histograms of Oriented Gradients（HOG） to describe the scene,and uses support vector machine to realize classification.Experimental result shows that the feature computation is accelerated and the classification accuracy of natural scene image is improved by using the improved method.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第21期182-184,共3页
Computer Engineering
基金
河南省基础与前沿技术研究计划基金资助项目(102300410113)
河南省重点科技攻关计划基金资助项目(092102210293)
关键词
梯度方向直方图
gist特征
自然场景
特征提取
自然场景分类
Histograms of Oriented Gradients（HOG）
gist feature
natural scene
feature extraction
natural scene classification
