2017 IEEE International Conference on Imaging Systems and Techniques (IST)最新文献_第8页

Automatic measurement based on stereo vision system using a single PTZ camera 基于立体视觉系统的单PTZ相机自动测量

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261469

Rui Wang, Suizhou Feng

{"title":"Automatic measurement based on stereo vision system using a single PTZ camera","authors":"Rui Wang, Suizhou Feng","doi":"10.1109/IST.2017.8261469","DOIUrl":"https://doi.org/10.1109/IST.2017.8261469","url":null,"abstract":"A parallel binocular stereo vision system and its application to dimensional measurement is introduced in this paper. The proposed system is established by controlling a single PTZ (pan-tilt-zoom) camera linear motion on a one dimensional precision displacement platform. To achieve accurate measurement results, an improved matching algorithm called as DC-SURF (Distortion Compensated-Speeded Up Robust Feature) by using adaptative filtering in terms of the image distortion during generating scale space is presented. Furthermore, the classic eight-point algorithm and the designed zoom strategy for PTZ camera are adopted for the measurement. The experimental results show that the proposed matching algorithm has better performance than other two classic matching algorithms over distorted images. Furthermore, the experiments demonstrate that without any reference materials the stereo vision dimensional measurement system proposed in this paper can be successfully applied to human height measurement with high precision. The results indicate a potential possibility of our approach to be used in other computer vision applications.","PeriodicalId":187213,"journal":{"name":"2017 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125035613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Parameters optimization of image sensor for star sensors 星敏感器图像敏感器参数优化

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261518

Yuanfang Liao, Xinguo Wei, Jian Li, Gangyi Wang

{"title":"Parameters optimization of image sensor for star sensors","authors":"Yuanfang Liao, Xinguo Wei, Jian Li, Gangyi Wang","doi":"10.1109/IST.2017.8261518","DOIUrl":"https://doi.org/10.1109/IST.2017.8261518","url":null,"abstract":"A star sensor realizes 3-axis attitude measurement by star imaging and star recognition, and is widely used for the spacecraft. Image sensor is the core device achieving photoelectric conversion (P-E) in the star sensor and its parameters such as exposure time and gain affect the performance of accuracy and dynamic. Therefore, a star sensor in the design phase is faced with the problem of how to determine the parameters of image sensor reasonably. The existing method for that is “trial and error method” that lacks the necessary theoretical basis. This paper proposes a parameters optimization method of image sensor for a star sensor. Firstly, the imaging model of star sensor, which has a clear physical meaning, is established, and the effect of imaging parameters on SNR is analyzed based on the corresponding theoretical derivation and simulations results. And the optimal parameters can be obtained when the SNR reaches the maximum value. Then results of experiments using a real star sensor, rotating platform and star simulator validate the simulations results. The summarized method in this paper should prove helpful for setting imaging parameters of other star sensors.","PeriodicalId":187213,"journal":{"name":"2017 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"41 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121003403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A new discontinuous synthetic aperture radar imaging framework 一种新的非连续合成孔径雷达成像框架

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261513

Yan Wang, Jian Yang, Jingwen Li

引用次数: 0

An airborne Position and Orientation System (POS) for remote sensing and its current state 一种用于遥感的机载定位系统及其现状

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261499

Zhai Fengguang, Ye Wen, Gu Bin, Lu Zhaoxing, Qiu Haitao, Jianli Li

引用次数: 2

Distributed compressive sensing for multi-baseline circular SAR image formation 多基线圆形SAR图像生成的分布式压缩感知

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261527

M. Farhadi, Chen Jie

{"title":"Distributed compressive sensing for multi-baseline circular SAR image formation","authors":"M. Farhadi, Chen Jie","doi":"10.1109/IST.2017.8261527","DOIUrl":"https://doi.org/10.1109/IST.2017.8261527","url":null,"abstract":"Circular Synthetic Aperture Radar (CSAR) can overcome some significant inherent drawbacks of conventional SAR imaging methods such as limited resolution and restricted aspect angle interval of the illuminated scene. In addition, utilizing of different elevation acquisition has the capability to reduce undesired sidelobes of single flight CSAR. Because of the sparse nature of elevation aperture data of multi baseline CSAR, sparse signal processing approaches have been employed instead of typical algorithms. firstly, the number of samples for recording and processing can be reduced significantly by subaperture acquisition. Moreover, sparsity driven approaches such as Compressive Sensing (CS) represents considerable sidelobe reduction. Whereas CS demonstrates adequate resolution, reducing the number of tracks degrades the ultimate image abruptly. Consequently, we exploit the novel idea of Distributed Compressive Sensing (DCS) with joint sparsity in this context to improve resolution and reduce sidelobe effect substantially in the consequent full aperture 3D image. Furthermore, implementation of the state-of-the-art sparsity-driven algorithm improve our imaging result and reduce computational burden.","PeriodicalId":187213,"journal":{"name":"2017 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126511094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Breast cancer detection with microwave imaging system using wearable conformal antenna arrays 采用可穿戴共形天线阵列的微波成像系统检测乳腺癌

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261547

Fengzhou Wang, T. Arslan, Guohua Wang

引用次数: 11

A CNN based volumetric imaging method with single X-ray projection 基于CNN的单x射线投影体成像方法

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261550

R. Wei, F. Zhou, Bo Liu, B. Liang, Bin Guo, Xuanang Xu

引用次数: 4

A platform for electrical capacitance tomography large-scale benchmark dataset generating and image reconstruction 电容层析成像大规模基准数据集生成与图像重建平台

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261465

Jin Zheng, Lihui Peng

引用次数: 3

An EIT image segmentation method based on projection distance minimization 一种基于投影距离最小化的EIT图像分割方法

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261447

Guanghui Liang, S. Ren, F. Dong

引用次数: 3

Simulation study of scaffold 3D cell culture imaging using a miniature planar EIT sensor 微型平面EIT传感器对支架三维细胞培养成像的模拟研究

2017 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2017-10-01 DOI: 10.1109/IST.2017.8261553

Yunjie Yang, Hancong Wu, J. Jia

引用次数: 2