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浏览/检索结果: 共5条，第1-5条 帮助 已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 基于消失点检测算法的束靶红外图像畸变校正 期刊论文 强激光与粒子束, 2023, 卷号: 35 作者:  陈丽萍;  许永建;  於子辰;  汪日新;  彭旭峰 收藏  |  浏览/下载：6/0  |  提交时间：2023/11/10 vanishing point detection  linear detection  image rectification  line segment clustering  neutral beam diagnosis  消失点检测  直线检测  图像校正  线段聚类  中性束诊断   Automatic comic page segmentation based on polygon detection 期刊论文 multimedia tools and applications, 2014 Li, Luyuan; Wang, Yongtao; Tang, Zhi; Gao, Liangcai 收藏  |  浏览/下载：4/0  |  提交时间：2015/11/10 Comic image segmentation  Polygon detection  Line clustering  Line segment detection  Integral image  DECOMPOSITION   Extraction of lane markings using orientation and vanishing point constraints in structured road scenes 期刊论文 International Journal of Computer Mathematics, 2014, 卷号: Vol.91 No.11, 页码: 2359-2373 作者:  Liu, Weirong;  Li, Shutao;  Huang, Xu 收藏  |  浏览/下载：2/0  |  提交时间：2019/12/31 lane detection  Laplacian filter  line segment detector  K-means clustering  intelligent vehicle  68T45  62H30  68U10   线段的三步快速聚类算法 期刊论文 电子测试, 2013, 期号: 11, 页码: 61-63,72 柳有权; 苏仙鹤 收藏  |  浏览/下载：22/0  |  提交时间：2013/09/17 线段聚类  结构特征  距离  方向  合并分离  line segment clustering  structure feature  distance  direction  merging or splitting   A segment detection method based on improved Hough transform (EI CONFERENCE) 会议论文 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China Han Q.-L.; Zhu M.; Yao Z.-J. 收藏  |  浏览/下载：18/0  |  提交时间：2013/03/25 Hough transform is recognized as a powerful tool in shape analysis which gives good results even in the presence of noise and the disconnection of edge. However  3. applying the standard Hough transform equation to every point of the input image edge  4. according to the local threshold  6. merging the segments whose extreme points are near. Experiment results show the approach not only can recognize regular geometric object but also can extract the segment feature of real targets in complex environment. So the proposed method can be used in the target detection of complicated scenes  traditional Hough transform can only detect the lines  2. quantizing the parameter space  and extracting a group of maximums according to the global threshold  eliminating spurious peaks which are caused by the spreading effects  and will improve the precision of tracking.  cannot give the endpoints and length of the line segments and it is vulnerable to the quantization errors. Based on the analysis of its limitations  Hough transform has been improved in order to detect line segment feature of targets. The algorithm aims to avoid the loss of spatial information  as well as to eliminate the spurious peaks and fix on the line segments endpoints accurately  5. fixing on the endpoints of the segments according to the dynamic clustering rule  which can expediently be used for the description and classification of regular objects. The method consists of 6 steps: 1. setting up the image  parameter and line-segment spaces