[1]黄鼎键,江灏,钟勇.复杂场景下基于视觉的非完整车位识别的算法改进[J].福建理工大学学报,2024,22(01):54-57.[doi:10.3969/j.issn.2097-3853.2024.01.008]
 HUANG Dingjian,JIANG Hao,ZHONG Yong.Algorithm improvement of vision-based incomplete parking space recognition in complex scenes[J].Journal of Fujian University of Technology;,2024,22(01):54-57.[doi:10.3969/j.issn.2097-3853.2024.01.008]
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复杂场景下基于视觉的非完整车位识别的算法改进
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《福建理工大学学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第22卷
期数:
2024年01期
页码:
54-57
栏目:
出版日期:
2024-02-25

文章信息/Info

Title:
Algorithm improvement of vision-based incomplete parking space recognition in complex scenes
作者:
黄鼎键江灏钟勇
(福建理工大学)福建省汽车电子与电驱动技术重点实验
Author(s):
HUANG Dingjian JIANG Hao ZHONG Yong
Fujian Key Laboratory for Automotive Electronics and Electric Drive Technology, Fujian University of Technology
关键词:
复杂场景视觉车位识别连通域分析
Keywords:
complex scenes vision parking space recognition connected component analysis
分类号:
TP242
DOI:
10.3969/j.issn.2097-3853.2024.01.008
文献标志码:
A
摘要:
为提高复杂场景下非完整车位识别的准确性,提出了一种基于视觉的车位识别改进算法。该识别算法采用了限制对比度自适应直方图均衡化方法,增强了图像细节;通过设置感兴趣区域和全局阈值分割法,区分了车位和背景、减少了车位周围环境噪声对车位识别的影响;利用形态学和连通域分析,排除了车位上的细小噪声和其他剩余噪声;结合Canny 边缘检测标记车位线轮廓边缘点,在原图上绘制准确的车位线轮廓。不同复杂环境下开展了非完整车位识别的试验,试验结果表明,所提出的改进算法相对于传统车位识别算法能够更准确地识别非完整车位,且具有较好的适应性和实时性。
Abstract:
In order to enhance the accuracy of incomplete parking space recognition in complex scenes, an improved vision-based parking space recognition algorithm was proposed. This recognition algorithm adopts a contrast-limited adaptive histogram equalization method to enhance image details. By setting regions of interest and using the global threshold segmentation method, the parking spaces and backgrounds are distinguished, and the impact of ambient noise around parking spaces on parking recognition is reduced. Morphology and connec-ted component analysis are utilized to eliminate other small noises and residual noises on the parking space. Combined with Canny edge detection, the edge points of the parking line contour are marked, and the accurate parking line contour is drawn on the original image. Experiments were conducted on incomplete parking space recognition in different complex environments, and results show that compared with traditional parking space recognition algorithms, the proposed improved algorithm can identify incomplete parking spaces more accurately and has better adaptability and real-time performance.

参考文献/References:

[1] ZHANG J D,LIU T,YIN X L,et al. An improved parking space recognition algorithm based on panoramic vision[J]. Multimedia Tools and Applications,2021,80(12):18181-18209.[2] 田海勇,王靖岳,王若羽,等. 基于边缘编组的车位线检测方法[J]. 科学技术与工程,2022,22(31):13988-13994.[3] 江浩斌,王成雨,马世典,等. 基于图像梯度匹配的自动泊车系统车位识别方法[J]. 江苏大学学报(自然科学版),2020,41(6):621-626.[4] 张悦旺. 基于改进Hough变换的车位线识别方法[J]. 计算机工程与设计,2017,38(11):3046-3050.[5] 姜武华,辛鑫,陈无畏,等. 基于信息融合的自动泊车系统车位线车位识别和决策规划[J]. 中国机械工程,2020,31(10):1190-1196.[6] LI Y Y,MAO H Y,YANG W,et al. Research on parking space status recognition method based on computer vision[J]. Sustainability,2022,15(1):107.[7] HUANG C,YANG S Y,LUO Y G,et al. Visual detection and image processing of parking space based on deep learning[J]. Sensors,2022,22(17):6672.[8] MA S D,FANG W F,JIANG H B,et al. Parking space recognition method based on parking space feature construction in the scene of autonomous valet parking[J]. Applied Sciences,2021,11(6):2759.[9] 张成涛,覃立仁,杨航,等. 自动泊车关键技术研究进展综述[J]. 汽车工程学报,2023,13(5):603-614.[10] ZHANG X,ZHAO W,JIANG Y Q. Study on parking space recognition based on improved image equalization and YOLOv5[J]. Electronics,2023,12(15):3374.[11] 苗作华,朱良建,赵成诚,等. 基于Retinex的低光照车位图像增强[J]. 汽车工程,2023,45(6):989-996.[12] 李尧,王彦. 基于全局阈值分割及多项式拟合的车道线识别[J]. 南华大学学报(自然科学版),2021,35(1):77-82,96.[13] 黄晨,刘泽,罗禹贡,等. 基于背景光照去除和连通区域的车位检测[J]. 汽车工程,2020,42(1):47-51,73.[14] 董翼宁,曹景胜,孙飞宇,等. 基于OpenCV图像处理的车道线识别研究[J]. 仪器仪表与分析监测,2023(3):29-32.

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更新日期/Last Update: 2024-02-25