2013 IEEE International Conference on Imaging Systems and Techniques (IST)最新文献_第3页

A gradient method used to identify object boundary in EIT image 一种用于EIT图像中目标边界识别的梯度方法

2013 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2013-10-01 DOI: 10.1109/IST.2013.6729726

Ruofan Wang, Liwen Miao, Yixin Ma

{"title":"A gradient method used to identify object boundary in EIT image","authors":"Ruofan Wang, Liwen Miao, Yixin Ma","doi":"10.1109/IST.2013.6729726","DOIUrl":"https://doi.org/10.1109/IST.2013.6729726","url":null,"abstract":"With the development of electronic technology and image reconstruction algorithm, the quality of EIT image is improved significantly. EIT technology has the potential to be of great value in medical and industrial applications. However, there is very little research about the estimation of anomaly's boundary from EIT image. The gradient method is proposed in this paper to identify object boundary from EIT image reconstructed by sensitivity conjugate gradient (SCG) algorithm. The performance of gradient method in terms of position error and size error is compared with traditional threshold method at two threshold levels through computer simulation and phantom experiments. The results show that the result of gradient method can cover the anomaly region in investigated situations and rely on very little priori-knowledge, while threshold method can estimate more accurately if the threshold value is set properly based on priori-knowledge. Improper threshold definition may lead to significant error in boundary identification. The pilot study to estimate the location and size of the anomaly from EIT image further completes EIT research and promotes its practical application.","PeriodicalId":448698,"journal":{"name":"2013 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125823740","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: 0

Automated detection of Optic Disc for the analysis of retina using color fundus image 利用彩色眼底图像分析视盘的自动检测

2013 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2013-10-01 DOI: 10.1109/IST.2013.6729698

Muhammad Zubair, Abubakar Yamin, S. Khan

引用次数: 26

Refined cartesian mesh for modeling in electrical capacitance tomography 电容层析成像中的精细笛卡尔网格建模

2013 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2013-10-01 DOI: 10.1109/IST.2013.6729724

W. Smolik, J. Kryszyn

引用次数: 2

A vein image enhancement algorithm for the multi-spectral illumination 一种多光谱照明下的静脉图像增强算法

2013 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2013-10-01 DOI: 10.1109/IST.2013.6729716

Zhaoguo Wu, Ya Zhou, Xiaoming Hu, Muqing Zhou, Xiaobing Dai, Xinzhou Li, Danting Wang

引用次数: 6

Handwritten digits recognition using a high level network-based approach 手写体数字识别采用高层次的基于网络的方法

2013 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2013-10-01 DOI: 10.1109/IST.2013.6729700

T. C. Silva, Liang Zhao

{"title":"Handwritten digits recognition using a high level network-based approach","authors":"T. C. Silva, Liang Zhao","doi":"10.1109/IST.2013.6729700","DOIUrl":"https://doi.org/10.1109/IST.2013.6729700","url":null,"abstract":"Complex networks refer to large-scale graphs with nontrivial connection patterns. The salient and interesting features that the complex network study offers in comparison to graph theory are the emphasis on the dynamical properties of the networks and the ability of inherently uncovering pattern formation of the vertices. In this paper, we present a hybrid data classification technique combining a low level and a high level classifier. The low level term can be equipped with any traditional classification techniques, which realize the classification task considering only physical or topological features (e.g., geometrical or statistical features) of the input data. On the other hand, the high level term has the ability of detecting data patterns with semantic meanings. In this way, the classification is realized by means of the extraction of the underlying network's features constructed from the input data. As a result, the high level classification process measures the compliance of the test instances with the pattern formation of the training data. Out of various high level perspectives that can be utilized to capture semantic meaning, we utilize the dynamical features that are generated from a tourist walker in a networked environment. Specifically, a weighted combination of transient and cycle lengths generated by the tourist walk is employed for that end. A study on the critical memory length is provided. Finally, we apply the proposed technique to the recognition of handwritten digit images and promising results have been obtained.","PeriodicalId":448698,"journal":{"name":"2013 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121497787","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

Industrial character recognition based on grid feature and wavelet moment 基于网格特征和小波矩的工业字符识别

2013 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2013-10-01 DOI: 10.1109/IST.2013.6729662

Yong Zhang, Sanxia Xie, Shulin Wei

{"title":"Industrial character recognition based on grid feature and wavelet moment","authors":"Yong Zhang, Sanxia Xie, Shulin Wei","doi":"10.1109/IST.2013.6729662","DOIUrl":"https://doi.org/10.1109/IST.2013.6729662","url":null,"abstract":"A novel descriptor for laser printing character recognition is proposed by using the fusion features and multilevel classification. There are two level features in the feature extraction module, the first level feature uses the coarse grid statistical features, having great applicability for local character distortion and stroke thickness inequality. Wavelet moment, as the second level feature, has the scale, translation and rotation invariance and the great anti-noise capability. It can reflect the approximation of the overall character and local detail information at the same time, so it is suitable for classing similar characters. As for the classification module, based on results of primary feature template matching classification in the first place, the second matching uses two level features fusion and special distortion character template to classify the top three character in the results. Experimental results demonstrate that using the fusion features and multilevel classification, industrial laser character recognition rate can be up to 99.2%, which is better than that of using single stage feature recognition.","PeriodicalId":448698,"journal":{"name":"2013 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128711577","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: 4

A novel CMOS image sensor using an output voltage feedback with variable dynamic range 采用可变动态范围输出电压反馈的新型CMOS图像传感器

2013 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2013-10-01 DOI: 10.1109/IST.2013.6729729

M. Bae, S. Jo, Hee-Ho Lee, Minho Lee, Juyeong Kim, P. Choi, Jang-Kyoo Shin, Seung Soo Kim, Jeongyeob Kim

引用次数: 0

Evaluation of effect of number of electrodes in ERT sensors on image quality ERT传感器中电极数对图像质量影响的评价

2013 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2013-10-01 DOI: 10.1109/IST.2013.6729655

Jiamin Ye, Haigang Wang, Wuqiang Yang

引用次数: 13

CT segmentation based on MRI images in context of prostate radiotherapy planning 基于MRI图像的CT分割在前列腺放疗规划中的应用

2013 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2013-10-01 DOI: 10.1109/IST.2013.6729685

A. Skalski, P. Kedzierawski, T. Zielinski, T. Kuszewski

引用次数: 2

Block-based compressive low-light-level imaging 基于块的压缩微光成像

2013 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2013-10-01 DOI: 10.1109/IST.2013.6729712

J. Ke, Ping Wei, Xin Zhang, E. Lam

引用次数: 5