Cognitive study of robot feasible region in unknown environment

CHEN Geng; LI Qing; SHI Jia-bin; WANG Chao-jie

doi:10.13873/J.1000-9787(2015)01-0066-03

Chinese

您当前的位置：

首页 >

文章列表页 >

Cognitive study of robot feasible region in unknown environment

更新时间：2025-09-11

- Cognitive study of robot feasible region in unknown environment
- Vol. 34, Issue 1, Pages: 66-68+72(2015)
- 作者机构：
  
  北京信息科技大学高动态导航技术北京市重点实验室
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2015)01-0066-03
  CLC： TP391.41
- Published：2015
- 稿件说明：
移动端阅览
[1]陈庚,李擎,时佳斌,王超杰.未知环境中机器人可行区域的认知研究[J].传感器与微系统,2015,34(01):66-68+72.

CHEN Geng, LI Qing, SHI Jia-bin, et al. Cognitive study of robot feasible region in unknown environment[J]. 2015, 34(1): 66-68+72.
[1]陈庚,李擎,时佳斌,王超杰.未知环境中机器人可行区域的认知研究[J].传感器与微系统,2015,34(01):66-68+72. DOI： 10.13873/J.1000-9787(2015)01-0066-03.

CHEN Geng, LI Qing, SHI Jia-bin, et al. Cognitive study of robot feasible region in unknown environment[J]. 2015, 34(1): 66-68+72. DOI： 10.13873/J.1000-9787(2015)01-0066-03.

摘要

针对未知环境中无人车对可行区域的认知

提出了一种结合分水岭算法、边缘提取、区域合并等思想的图像分割方法。利用图像的灰度信息进行分水岭变化后

将图像过分割成多个小区域;再根据边缘信息所在位置对这些小区域进行初步区域合并。最后利用区域邻接图和图像的色调、亮度、灰度等信息描述剩余区域间的关系

将2个相邻区域的色调和灰度差值关系作为权值函数

根据亮度信息寻找阈值。实验结果表明:该方法有效提高了区域合并的准确性

成功分割出可行区域

为无人车的自主行驶提供了有力的保障。

Abstract

Aiming at need of the cognitive of unmanned vehicles feasible region in unknown environments

propose an algorithm for image segmentation that combines of watershed algorithm

edge detection and region merging. After the watershed using the gray information of the image

it is divided into a number of smaller area.Then according to the location information of the edge carries out preliminary region merging of these small area.Finally using hue

brightness

grayscale and region adjacency graph information describe the relationship between the remaining areas. The tones and gray of two adjacent regions as the weight function and finding a threshold value based on luminance information. Experimental results show that this method effectively improves the accuracy of the regional merger and successfully segment the feasible region. The theory provides a strong guarantee for the unmanned vehicle autonomous driving.

关键词

Keywords

references

一种参数化的形态学分水岭图像分割方法 [J]. 王小鹏,党建武,王阳萍. 铁道学报 . 2013(01)

基于改进的变分水平集和区域生长的图像分割方法的研究 [J]. 姜慧研,冯锐杰. 电子学报 . 2012(08)

基于邻接表的分水岭变换快速区域合并算法 [J]. 李苏祺,张广军. 北京航空航天大学学报 . 2008(11)

基于分水岭变换和图论的图像分割方法 [J]. 冯林,孙焘,吴振宇,管慧娟. 仪器仪表学报 . 2008(03)

彩色图像分割方法综述 [J]. 林开颜,吴军辉,徐立鸿. 中国图象图形学报 . 2005(01)

Interactive image segmentation by maximal similarity based region merging [J] . Jifeng Ning,Lei Zhang,David Zhang,Chengke Wu. Pattern Recognition . 2009 (2)

Color image segmentation based on adaptive local thresholds [J] . Ety Navon,Ofer Miller,Amir Averbuch. Image and Vision Computing . 2004 (1)

Views

186

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Character paper-cutting design based on convolutional neural network

Blood serum level detection in blood-collecting vessel based on image recognition

Color image segmentation based on disjunctive normal level set

Application of improved watershed algorithm in TBM rock identification and measurement

A pore detection algorithm based on joint feature constraint

Related Author

YAO Chao

LIU Guihua

ZHAO Sen

LIN Jie

LIU Cong

WANG Chao

HOU Jianping

ZHAO Wanli

Related Institution

College of Public Administration,University of Electronic Science and Technology of China

Sichuan Key Laboratory of Special Environment Robot Technology

College of Information Engineering,Southwest University of Science and Technology

Autobio Labtec Instruments Co Ltd

Hubei Agricultural Machinery Engineering Research and Design Institute,Hubei University of Technology

⁰