融合式空间塔式算子和HIK-SVM的交通标志识别研究  

Traffic Sign Recognition Based on Pyramid Histogram Fusion Descriptor and HIK-SVM

作　　者：刘亚辰[1] 陈跃鹏[1] 张赛硕 肖文超[1] 

机构地区：[1]武汉理工大学自动化学院,武汉430070

出　　处：《交通运输系统工程与信息》2017年第1期220-226,共7页Journal of Transportation Systems Engineering and Information Technology

基　　金：国家自然科学基金(61374151)~~

摘　　要：在交通标志识别问题上,提出了一种基于融合式的空间塔式算子和直方图交叉核支持向量机(HIK-SVM)的分类方法.在该方法中,通过提取图像的灰度塔式词袋直方图(Gray-PHOW)特征、颜色塔式词袋直方图(Color-PHOW)特征和塔式边缘方向梯度直方图(PHOG)特征来对交通标志的外观、颜色和轮廓信息进行描述.通过提取空间塔式直方图特征,能很好地对图像各种特征的空间分布状况进行描述.提取到图像的外观、颜色、轮廓和特征的空间分布信息后,对其进行融合,最后得到的融合式的空间塔式特征具有很强的鲁棒性.将该融合式特征送入HIK-SVM进行训练和分类,取得了极其高的识别效果.A recognition method is proposed based on the fusion of the spatial pyramid descriptor and the histogram intersection kernel support vector machine（HIK-SVM） on the identification of traffic signs.The appearance, color and contour information of traffic sign characteristics are described by extracting descriptor of gray pyramid histogram of visual words（Gray-PHOW）, color pyramid histogram of visual words（Color-PHOW） and pyramid histogram of edge orientations gradients（PHOG） in this method.Spatial distribution of various features of the images can be well described by extracting the descriptor of the spatial pyramid histogram.Integrated them after extracting the spatial information of the image in terms of appearance, color, contour profile and feature, then strong robustness is embodied in space pyramid feature with integrated style.After the integrated feature is sent to HIK-SVM for training and classification, very high recognition rate could be achieved.

关 键 词：智能交通 交通标志识别 塔式词袋直方图 塔式边缘方向梯度直方图 支持向量机 DENSE SIFT 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]