J4 ›› 2012, Vol. 34 ›› Issue (6): 123-126.
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曹 磊，李璟，洪留荣
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基金资助:
安徽省教育厅自然科学基金资助项目（KJ2012Z354）
CAO Lei,LI Jing,HONG Liurong
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摘要：
为了提高车辆识别的效率，本文提出了一种基于车辆多种局部特征的融合识别算法。算法采用优化的PCA方法对车辆的多种局部特征进行抽取、分析及融合来实现车辆的识别检测。实验结果表明，该算法可有效降低车辆阴影及周围环境对识别效率的影响，提高车辆在部分遮挡情况下的检测效率，具有较好的精确性和稳定性。
关键词: 车辆检测, 特征区域, PCA, 灰度均衡
Abstract:
In order to improve the efficiency of vehicle recognition, this paper puts forward a fusion recognition algorithm based on a variety of local features of the vehicles. The algorithm adopts the optimized Principal Component Analysis (PCA) to extract, analyze, and fuse the local features of the vehicles so as to realize the recognition of vehicles. The results of the experiments indicate that the algorithm can effectively reduce the influence of the shadows of vehicles and the surrounding environment, and improve the recognition efficiency under the circumstance of partial blocking of a vehicle, and that the algorithm has pretty good accuracy and stability.
Key words: vehicle detection;feature region;PCA;gray balance
曹 磊，李璟，洪留荣. 一种融合区域化多特征的车辆检测方法[J]. J4, 2012, 34(6): 123-126.
CAO Lei,LI Jing,HONG Liurong. A Vehicle Recognition Method Based on Regional MultiFeature Fusion[J]. J4, 2012, 34(6): 123-126.
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http://joces.nudt.edu.cn/CN/Y2012/V34/I6/123
