Localize car door handles with image segmentation and saliency detection

Fan Zhang, Mengchao Hao, Muyang Liu, Jinyu Yang
{"title":"Localize car door handles with image segmentation and saliency detection","authors":"Fan Zhang, Mengchao Hao, Muyang Liu, Jinyu Yang","doi":"10.1109/IST.2017.8261539","DOIUrl":null,"url":null,"abstract":"Importance of little objects in cars such as door handles is obvious, both in daily lives and in industrial manufacture. However, since the lack of the distinctive appearance and feature, obtaining the location of them is still remaining a challenge. This paper proposes an effective approach for the detection of the door handles of cars. The method innovatively combines frequency and spatial domains' algorithms to detect the location of little objects of cars in a relatively large image. To illustrate the method more concisely, our method localizes door handles through image segmentation and visual saliency detection. First, by segmenting the image we can remove the unnecessary area to improve the speed and accuracy of our approach. After finding the region of interest, our approach uses a visual saliency detection algorithm named Spectral Residual Approach which can get the location of door handles accurately. At last, the approach is tested by different kinds of images of vehicles. The results of the experiments show that our approach is obvious and practical.","PeriodicalId":187213,"journal":{"name":"2017 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Imaging Systems and Techniques (IST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IST.2017.8261539","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Importance of little objects in cars such as door handles is obvious, both in daily lives and in industrial manufacture. However, since the lack of the distinctive appearance and feature, obtaining the location of them is still remaining a challenge. This paper proposes an effective approach for the detection of the door handles of cars. The method innovatively combines frequency and spatial domains' algorithms to detect the location of little objects of cars in a relatively large image. To illustrate the method more concisely, our method localizes door handles through image segmentation and visual saliency detection. First, by segmenting the image we can remove the unnecessary area to improve the speed and accuracy of our approach. After finding the region of interest, our approach uses a visual saliency detection algorithm named Spectral Residual Approach which can get the location of door handles accurately. At last, the approach is tested by different kinds of images of vehicles. The results of the experiments show that our approach is obvious and practical.
利用图像分割和显著性检测对车门把手进行定位
无论是在日常生活中还是在工业生产中,像门把手这样的汽车小物件的重要性都是显而易见的。然而,由于缺乏鲜明的外观和特征,获取它们的位置仍然是一个挑战。本文提出了一种有效的汽车门把手检测方法。该方法创新地结合了频率域和空间域算法,在较大的图像中检测汽车小物体的位置。为了更简洁地说明该方法,我们的方法通过图像分割和视觉显著性检测来定位门把手。首先,通过分割图像,我们可以去除不必要的区域,以提高我们的方法的速度和准确性。在找到感兴趣的区域后,我们的方法使用了一种名为光谱残差法的视觉显著性检测算法,该算法可以准确地获得门把手的位置。最后,用不同类型的车辆图像对该方法进行了验证。实验结果表明,该方法具有明显的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书