计算机工程与应用Issue(9)：147-151,5.DOI:10.3778/j.issn.1002-8331.1407-0279
基于证据理论融合多特征的物体识别算法
Object recognition method based on multi-feature fusion of D-S evidence theory
摘要
Abstract
In order to obtain better recognition results, a novel object recognition method based on multi-feature fusion of evidence theory is proposed. Color histogram and scale invariant feature transform features are extracted from object image, and extreme learning machine is used to establish the classifier;the recognition results of single feature are fused to obtain the last recognition results of object based on evidence theory;the performance of algorithm is tested by some image data. The result illustrates that the proposed algorithm has improved the recognition rate and speed, and it has some application vale.关键词
物体识别/证据理论/极限学习机/尺度不变特征变换/颜色直方图Key words
object recognition/evidence theory/extreme learning machine/scale invariant feature transform/color histogram分类
信息技术与安全科学引用本文复制引用
孙晋博,余隋怀,陈登凯..基于证据理论融合多特征的物体识别算法[J].计算机工程与应用,2015,(9):147-151,5.基金项目
国家高技术研究发展计划（863）（No.2009AA093303）；高等学校学科创新引智计划（No.B13044）。 （）
