机构

• 长春光学精密机械与物... [1]
• 自动化研究所 [1]

采集方式

• OAI收割 [2]

内容类型

• 会议论文 [1]
• 期刊论文 [1]

发表日期

• 2021 [1]
• 2006 [1]

学科主题

筛选

浏览/检索结果: 共2条，第1-2条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 A Model of Spray Tool and a Parameter Optimization Method for Spraying Path Planning 期刊论文  OAI收割 International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 1017-1031 作者:  Ruxiang Hua;  Wei Zou;   Guodong Chen;  Hongxuan Ma;  Wei Zhang   |  收藏  |  浏览/下载：17/0  |  提交时间：2023/07/04 Digital camouflage  spraying robot  path optimization  parameter setting  coating thickness uniformity   A segment detection method based on improved Hough transform (EI CONFERENCE) 会议论文  OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者:  Yao Z.-J. 收藏  |  浏览/下载：24/0  |  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