计算机技术与发展Issue(1)：26-30,5.DOI:10.3969/j.issn.1673-629X.2014.01.007
基于学习的霍夫变换线段组物体检测算法
An Object Detection Algorithm of Hough Transform Line Segmentation Groups Based on Learning
摘要
Abstract
Aiming at the problems of the weak distinguishing ability for the algorithm based on single Hough Transform Line Segment ( HTLS) feature,which cannot effectively deal with partial matching,an algorithm of the HTLS groups is proposed. Firstly in this paper, the algorithm extracts the Hough transform line segment feature to constitute the codebook as input of weak detector. Then through the study of AdaBoost algorithm make weak detectors structure into a strong detector,in order to improve the efficiency of detection. The fi-nal tests on the test set. To calculate the similarity between the two Hough transform line segment,a weighted Euclidean distance is intro-duced,through adjusting the weights,can effectively deal with unreliable edge detection problem. The experiment shows that the algorithm can deal with the partial sheltering problem,has a very good development potential.关键词
物体检测/霍夫变换/局部特征/图像匹配/AdaBoostKey words
object detection/Hough transform/partial feature/image matching/AdaBoost分类
信息技术与安全科学引用本文复制引用
郑权,刘循,魏海明..基于学习的霍夫变换线段组物体检测算法[J].计算机技术与发展,2014,(1):26-30,5.基金项目
国家自然科学基金资助项目(61173099) （61173099）
国家“863”高技术发展计划项目(2012AA011804) （2012AA011804）
