ROI Based Post Image Quality Assessment Technique on Multiple Localized Filtering Method on Kinect Sensor

Kholilatul Wardani, A. Kurniawan, E. Mulyana, Hendrawan
{"title":"ROI Based Post Image Quality Assessment Technique on Multiple Localized Filtering Method on Kinect Sensor","authors":"Kholilatul Wardani, A. Kurniawan, E. Mulyana, Hendrawan","doi":"10.1109/TSSA.2018.8708810","DOIUrl":null,"url":null,"abstract":"Region of Interest (ROI) Image Quality Assessment is an image quality assessment model based on Structural Similarity Index (SSI) used in the specific designated image region to be assessed. The output assessment value used by this image assessment model is 1 which means identical and -1 which means not identical. The assessment model of ROI Quality Assessment in this research is used to measure image quality on Kinect sensor capture result used in Mobile HD Robot after applying Multiple Localized Filtering Technique. The filter is applied to each capture sensor depth result on Kinect, aiming to eliminate structural noise which occurs in the Kinect sensor. Assessment is done by comparing the image quality before and after filter applied to certain regions. The Kinect sensor will be conditioned to capture a square black object measuring 10cm x 10cm perpendicular to a homogeneous background (white with RGB code 255,255,255). The results of Kinect sensor data will be taken through EWRF 3022 by visual basic 6.0 program periodically, 10 times each session with frequency 1 time per minute. The results of this trial show the same similar index (value 1: identical) in the luminance, contrast and structural section of the edge region or edge region of the specimen. The value indicates that the Multiple Localized Filtering Technique is applied to the noise generated by the Kinect sensor. Based on the ROI Image Quality Assessment model, there is no effect on the image quality generated by the sensor.","PeriodicalId":159795,"journal":{"name":"2018 12th International Conference on Telecommunication Systems, Services, and Applications (TSSA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 12th International Conference on Telecommunication Systems, Services, and Applications (TSSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSSA.2018.8708810","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Region of Interest (ROI) Image Quality Assessment is an image quality assessment model based on Structural Similarity Index (SSI) used in the specific designated image region to be assessed. The output assessment value used by this image assessment model is 1 which means identical and -1 which means not identical. The assessment model of ROI Quality Assessment in this research is used to measure image quality on Kinect sensor capture result used in Mobile HD Robot after applying Multiple Localized Filtering Technique. The filter is applied to each capture sensor depth result on Kinect, aiming to eliminate structural noise which occurs in the Kinect sensor. Assessment is done by comparing the image quality before and after filter applied to certain regions. The Kinect sensor will be conditioned to capture a square black object measuring 10cm x 10cm perpendicular to a homogeneous background (white with RGB code 255,255,255). The results of Kinect sensor data will be taken through EWRF 3022 by visual basic 6.0 program periodically, 10 times each session with frequency 1 time per minute. The results of this trial show the same similar index (value 1: identical) in the luminance, contrast and structural section of the edge region or edge region of the specimen. The value indicates that the Multiple Localized Filtering Technique is applied to the noise generated by the Kinect sensor. Based on the ROI Image Quality Assessment model, there is no effect on the image quality generated by the sensor.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于ROI的Kinect传感器多局部滤波后图像质量评价技术
感兴趣区域(Region of Interest, ROI)图像质量评估是一种基于结构相似指数(Structural Similarity Index, SSI)的图像质量评估模型,用于特定的待评估图像区域。本图像评价模型使用的输出评价值为1,表示相同,-1表示不相同。本研究的ROI质量评估评估模型用于测量移动高清机器人使用的Kinect传感器捕获结果在应用多重局部滤波技术后的图像质量。该滤波器应用于Kinect上的每个捕获传感器深度结果,旨在消除Kinect传感器中出现的结构噪声。评估是通过比较应用于特定区域的滤波前后的图像质量来完成的。Kinect传感器将被设定为捕捉一个垂直于均匀背景(白色,RGB代码为255,255,255)的10cm x 10cm的方形黑色物体。用visual basic 6.0程序定期通过EWRF 3022采集Kinect传感器数据的结果,每次10次,频率每分钟1次。本试验结果在试样的边缘区域或边缘区域的亮度、对比度和结构截面上显示相同的相似指数(值1:相同)。该值表示对Kinect传感器产生的噪声应用多重局部滤波技术。基于ROI图像质量评估模型,不影响传感器生成的图像质量。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Error Pointing Correction System Implemented in the Air Balloon Communication System Thin Clients as Memoryless Computer for Reducing Digital Divide in East Indonesia Design and Implementation of WebRTC-Based Video Conference System in Odroid Board Leveraging SDN for Handover in Distributed Mobility Management of 5G Network Assessment of IT Governance of Bakti Internet Access Program Based on the COBIT5 Framework : Case Study: Balai Latihan Kerja Kendari
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1