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机构地区:[1]吉林大学计算机科学与技术学院,长春130012
出 处:《吉林大学学报(工学版)》2013年第S1期128-132,共5页Journal of Jilin University:Engineering and Technology Edition
基 金:国家自然科学基金项目(61101155);吉林省科技发展计划资助项目(20101504);吉林省教育厅科学基金项目(2009604)
摘 要:为了实现对交通标识的快速准确识别,将颜色特征和形状特征相结合,利用特征融合提出图像快速检索算法。在颜色特征方面,改进了传统的颜色直方图方法,引入基于主色调的颜色直方图算法;针对道路交通标志特殊的语义特征,经过特征过滤筛选缩小搜索的范围。在形状特征方面,采用傅里叶形状描述,突出了轮廓线的切向角度(曲率),忽略了中心距及复坐标等因素,提高了识别速度。将颜色空间HSV特征和形状描述ART特征融合,提高识别率,同时适应复杂背景下交通标志识别。通过对颜色和形状特征间的权重λ进行调,通过VC6.0实现自主移动机器人平台测试。其准确率和实效性都达到实际应用效果。The design and implementation of an image retrieval system integrated multi-features through combining color and shape were realized in this paper.In the respect of color feature,some improvements were made to the traditional color histogram method,and a new color histogram method based on main colors was proposed.By combining the major color retrieving method and the color histogram computing,two quick screenings were carried out,thereby the scope of the search was narrowed and the retrieval efficiency was improved.With Fourier shape descriptors adopted,an improved contour-based description method was proposed.Because the tangential angle of contours(curvature) was highlighted and factors such as complex coordinates and center distance were ignored,within a reasonable range,the accuracy was lowered appropriately and the query speed was improved significantly.Finally,the fusion of the HSV feature and ART feature,improved the retrieval accuracy of road traffic signs.Autonomous mobile robot platform was realized in VC 6.0.Experiments show that,if combining the features of the color and shape together,adjusting the weighting coefficient λ between the two,ultimately the value of λ can be determined,the recall ratio and precision ratio reach a relatively higher level.
关 键 词:图像检索 颜色特征 形状特征 多特征匹配 交通标识识别
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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