基于梯度幅度和Hough变换的林木根系GPR目标检测  

Tree root GPR target detection based on the gradient magnitude and modified Hough transform

作　　者：宋文龙[1] 杨鑫[1] 李克新[1] 贾鹤鸣[1] 

机构地区：[1]东北林业大学机电工程学院

出　　处：《北京林业大学学报》2013年第6期108-112,共5页Journal of Beijing Forestry University

基　　金：国家自然科学基金项目(31270757);中央高校基本科研业务费专项(DL12DB05;DL13BB14);新世纪优秀人才支持计划项目(NCET-09-0279);高等学校博士学科点专项(20120062120008;20110062110002)

摘　　要：探地雷达图像中识别林木根系的重要依据是双曲线回波特征。通过分析精确检测到的林木根系探地雷达图像中的双曲线,提出了目标曲线检测的改进方法。该方法包括2个方面的内容:1)基于探地雷达图像具有子波频率信息的特殊性,提出了一种基于梯度幅度的感兴趣区域(ROI)提取方法,为了使梯度幅度图中双曲线特征更为突出,对普通梯度法进行了微分取值方式的优化,实现了双曲线的快速提取;2)对提取出来的ROI进行Hough变换以检测双曲线,通过位置信息与幅度信息综合投票提高原始Hough变换的精确度,去除背景杂波等虚假目标,从而实现目标双曲线的精确提取。The hyperbolic echo feature is one of the most important elements for root recognition in ground penetrating radar （GPR） image. By intensive analysis of the hyperbola detected accurately from tree root image by GPR, an improved method was presented to detect the target curve. The new method includes two aspects of content ： 1 ） According to the particularity of GPR image＇s wavelet spectrum information, an extraction method of region of interest （ROI） was proposed based on GPR gradient magnitude. Furthermore, in order to make the hyperbolic characteristics in the gradient magnitude diagram more outstanding, the way of differential value was optimized by gradient magnitude method to achieve the rapid extraction of hyperbolic. 2） Hough transform was conducted to detect the hyperbola in ROI. By using location information and amplitude information comprehensively voting, the accuracy of original Hough transform was improved, and the background clutters and false targets can be removed effectively. Noise immunity of the method proposed was strong. In addition, the stability of the method was high. Thereby the accurate extraction of the target hyperbola is realized.

关 键 词：探地雷达 林木根系 梯度幅度法 HOUGH变换 

分 类 号：S792.93[农业科学—林木遗传育种] TP391.4[农业科学—林学]