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基于决策树的海上搜救目标检测算法
引用本文:陈鹏鹏,冉鑫.基于决策树的海上搜救目标检测算法[J].上海海事大学学报,2010,31(3):1-4.
作者姓名:陈鹏鹏  冉鑫
作者单位:上海海事大学,商船学院,上海,200135
基金项目:国家高技术研究发展计划(“八六三”计划)(2007AA11Z249);上海市自然科学基金(08ZR1409300);上海市重点学科建设项目(S30602);上海市教育委员会支出预算项目(2008083)
摘    要:为克服传统目标识别方法在处理空间特征分布极为复杂的数据时的缺点,提出1种基于决策树的多特征检测算法,并将其应用到基于视频的海上搜救目标检测中.该算法首先提取图像中的颜色、亮度等信息,通过计算各特征的信息增益建立决策树,将搜救目标检测问题分解成3层决策树分类问题.实验表明,该算法能够提高多特征目标检测的效率,在救生艇、筏等海上搜救目标检测的应用中取得较好的结果.

关 键 词:目标检测    决策树    特征提取    图像处理
收稿时间:1/4/2010 2:33:14 PM
修稿时间:2010/5/10 0:00:00

Marine rescue target detection algorithm based on decision tree
Chen Pengpeng and Ran Xin.Marine rescue target detection algorithm based on decision tree[J].Journal of Shanghai Maritime University,2010,31(3):1-4.
Authors:Chen Pengpeng and Ran Xin
Institution:Merchant Marine College, Shanghai Maritime University,Merchant Marine College, Shanghai Maritime University
Abstract:In order to overcome the shortcomings of the traditional target recognition method in dealing with the data of highly complex spatial characteristics distribution, a multi feature detection algorithm based on decision tree theory is proposed and applied to the marine rescue target detection based on video. In the algorithm, color, intensity and other information of the images are extracted firstly, then the decision tree is built by calculating the information gain of each feature, thus the detection of the rescue target is transformed into the classification process of three layer decision tree. Experiments indicate that the algorithm can improve the efficiency of multi feature target detection, and it works well in the rescue target detection such as lifeboat and life raft.
Keywords:target detection  decision tree  feature extraction  image processing
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