{"title":"Fast and robust automated segmentation of EIT lung images using an anatomically constrained Kalman filter","authors":"A. Zifan, P. Liatsis","doi":"10.1109/IST.2012.6295492","DOIUrl":"https://doi.org/10.1109/IST.2012.6295492","url":null,"abstract":"In this paper we present a new pipeline for the fast and accurate segmentation of impedance images of the lungs using Electrical Impedance Tomography (EIT). EIT is an emerging promising non-invasive imaging modality, which produces real-time poor-spatial but high temporal resolution images of impedance inside a body. Recovering impedance itself constitutes a non-linear ill-posed inverse problem, therefore the problem is usually linearized which produces impedance-change images rather than static impedance, and the images are highly blurry and fuzzy along the object boundaries. We provide a mathematical reasoning behind the high suitability of the Kalman filter when it comes to segmenting and tracking conductivity changes in EIT lung images. Next, we use a two-fold approach to tackle the segmentation problem. First, we construct a global lung shape to restrict the search region of the Kalman filter. Next, we proceed by augmenting the Kalman filter by incorporating an adaptive foreground detection system to provide the boundary contours for the Kalman filter to carry out the tracking of the conductivity changes as the lungs undergo deformation in a respiratory cycle.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"2005 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125807899","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}
{"title":"Secondary image reconstruction based on Associative Markov Networks for electrical resistance tomography","authors":"Jiamin Ye, B. Hoyle","doi":"10.1109/IST.2012.6295495","DOIUrl":"https://doi.org/10.1109/IST.2012.6295495","url":null,"abstract":"The images reconstructed by electrical resistance tomography for two-phase flow with distinctive phase origins are usually blurred at the phase interface. To improve the image quality, secondary image reconstruction with Associative Markov Networks (AMNs) is presented. The initial images are reconstructed by the Landweber iteration algorithm. The obtained images are then processed using AMNs. The weights of AMNs are learned by a quadratic program and then a min-cut is used for the maximum a posteriori inference to obtain the optimal images. Simulation results from both noise-free and noisy data show significant improvement in the phase interface of images. For some conductivity distributions, the image errors can be reduced to a fifth of the initial values.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"54 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129306284","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}
{"title":"Two-pass color interpolation for color filter array","authors":"Yi-Hong Yang, Po-Ning Chen, Peng-Hua Wang","doi":"10.1109/IST.2012.6295504","DOIUrl":"https://doi.org/10.1109/IST.2012.6295504","url":null,"abstract":"How to manufacture a low-cost digital still camera (DSC) that can meanwhile provide a good image quality is always an engineering challenge. For this purpose, the color filter array (CFA) is perhaps the most commonly used structure for modern DSCs. However, since most of the color information is filtered out, a good interpolation process is required to retrieve the original image. Many interpolation methods have thus been proposed. In this work, we propose to perform the edge-preserving signal correlation based (EP-SCB) interpolation [1] as a second pass to those images restored from some other existing interpolation methods such as local polynomial approximation intersection of confidence intervals (LPA-ICI) rule [2]. Experiments show that most of the images' PSNRs can be improved by the second pass. The simplicity of the EP-SCB hence makes it a suitable candidate as an enhancement option for DSCs techniques.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130950785","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}
{"title":"Estimation of adjacency effect in the remotely sensed Hyperspectral data over rugged scenes","authors":"Cheng Jiang, Huijie Zhao, Guorui Jia","doi":"10.1109/IST.2012.6295550","DOIUrl":"https://doi.org/10.1109/IST.2012.6295550","url":null,"abstract":"Adjacency Effect heavily affects the remotely sensed Hyperspectral data by adding surface surrounding scattering signals at sensor. Estimation of adjacency effect remains difficult because of the complex phenomena induced by rugged terrain. Indeed, existing method is not valid for a rough, heterogeneous surface like rugged terrain. In this paper we describe a method to estimate the adjacency effect in Hyperspectral data of rugged terrain. We compute the scattering and reflecting of light from adjacent surfaces into the field-of-view (FOV) based on the theory of radiation transfer. Our computation takes molecular/aerosol scattering phase functions and topographic features into account. We also discuss the dependence of the adjacency effect on the aerosol optical thickness and the relief of terrain.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128919596","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}
{"title":"Vision-based indoor occupants detection system for intelligent buildings","authors":"Dixin Liu, Youtian Du, Qianchuan Zhao, X. Guan","doi":"10.1109/IST.2012.6295489","DOIUrl":"https://doi.org/10.1109/IST.2012.6295489","url":null,"abstract":"In intelligent buildings, practical sensing systems designed to gather indoor occupancy information play an indispensable role in improving occupant comfort and energy efficiency by optimizing control strategies of HVAC (Heating, Ventilation and Air Conditioning) system and lighting system. In this paper we propose a novel method for occupant detection based on video surveillances now widely used in buildings. In our method, a two-staged static detector using both Haar-like and HOG (Histograms of Oriented Gradients) features and a template-based motion analysis module are concatenated to detect the heads of occupants rapidly and effectively. The accuracy can satisfy the requirements of the automation systems in intelligent buildings. Experimental results demonstrate the effectiveness and efficiency of the proposed method.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123790555","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}
{"title":"Quality measures for blind image deblurring","authors":"A. Khan, Hujun Yin","doi":"10.1109/IST.2012.6295559","DOIUrl":"https://doi.org/10.1109/IST.2012.6295559","url":null,"abstract":"Blind image deblurring is limited by the unavailability or in many cases little information about the PSF. If the PSF is estimated, then deblurring simplifies to just deconvolving the blurred image with the PSF using any conventional deblurring filter. We have recently proposed a blind deblurring scheme using kurtosis measures. The scheme is able to deblur degraded images of unknown types such as out-of-focus, motion or atmospheric turbulence. However, for blurred images whose original are unknown, it is impossible to measure the improvement, unlike in simulated blurring cases. In this paper, a way of measuring the quality improvement of the deblurring is suggested. The deblurred image is-reblurred by the estimated PSF and then the PSNR between the original blurred image and the re-blurred image is calculated as an indication of deblurring quality. Deblurring filters often produce noise and ringing artifacts in the deblurred image, which will be less severe when a candidate filter similar to the true PSF is used. This quality measures further enhance the blind deblurring scheme and has been tested on both synthetic and real blurred images.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115987802","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}
Hongcheng Wang, I. Fedchenia, S. Shishkin, A. Finn, L. Smith, M. Colket
{"title":"Electrical Capacitance Tomography: A compressive sensing approach","authors":"Hongcheng Wang, I. Fedchenia, S. Shishkin, A. Finn, L. Smith, M. Colket","doi":"10.1109/IST.2012.6295574","DOIUrl":"https://doi.org/10.1109/IST.2012.6295574","url":null,"abstract":"We present a new image reconstruction method for Electrical Capacitance Tomography (ECT). ECT image reconstruction is generally ill-posed because the number of measurements is small whereas the image dimensions are large. Here, Compressive Sensing is used to provide better reconstruction from the small number of measurements. Given the sparsity of the signal (image), the idea is to apply an efficient and stable algorithm through L1 regularization to recover the sparse signal with sufficient measurements that have cardinality comparable to the sparsity of the signal. In this paper, we present Total Variation (TV) regularization for ECT image reconstruction, and apply an efficient Split-Bregman Iteration (SBI) approach to solve the problem. We propose a joint metric of positive re-construction rate (PRR) and false reconstruction rate (FRR) to evaluate image reconstruction performance. The results on both synthetic and real data show that the proposed TV-SBI method can better preserve the edges of images and better resolve different objects within reconstructed images, as compared to a representative state-of-the-art ECT image re-construction algorithm, Projected Landweber Iteration with Linear Back Projection initialization (LBP-PLI).","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130619742","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}
{"title":"Effect of inclined angle of fuel jet on NOx emission in high temperature air combustion","authors":"Xiaolu Li, Zhongbao Wei, Lijun Xu, Yanting Cheng","doi":"10.1109/IST.2012.6295522","DOIUrl":"https://doi.org/10.1109/IST.2012.6295522","url":null,"abstract":"This paper investigates the effect of inclined angle of fuel jet on concentration of NOx emission in high temperature air combustion furnace. Computational Fluid Dynamics (CFD) modeling was implemented to investigate the combustion process and NOx formation in the furnace. The CFD model presented in this paper is validated by comparing the modeling results with measured data. The results show that the concentration of NOx emission decreases by increasing the inclined angle of fuel jet. Besides, the concentration of NOx emission drops with the decrease of oxygen concentration. Moreover, the effecting degree of inclined angle on NOx formation increases with the increase of oxygen concentration.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134337890","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}
Y. Tanimoto, H. Yamamoto, K. Namba, A. Tokuhiro, K. Furusawa, H. Ukida
{"title":"Imaging of the turn space and path of movement of a wheelchair for remodeling houses of individuals with SCI","authors":"Y. Tanimoto, H. Yamamoto, K. Namba, A. Tokuhiro, K. Furusawa, H. Ukida","doi":"10.1109/IST.2012.6295508","DOIUrl":"https://doi.org/10.1109/IST.2012.6295508","url":null,"abstract":"The houses of individuals with SCI (spinal cord injury) are remodeled according to their wheelchair operation ability, the method of body transfer, and their use of welfare equipment before they return from the hospital. In our rehabilitation center, house remodeling is demonstrated for individuals and family members using three-dimensional computer graphic images before the house construction is started. In this study, the turning radius is calculated using image sequences of the wheelchair that are estimated using the speeds of the motion of both the wheelchair rear wheels as measured using rotary encoders. The two-dimensional remodeled house image on which the turn space of the wheelchair is displayed is created using the individual's calculated turn radius of the wheelchair. Moreover, to design the toilet room, the path of motion and the image sequences of the wheelchair approaching and leaving the toilet are displayed on an image of the toilet room.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127634177","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}
{"title":"A generalized thresholding algorithm of pedestrian segmentation for far-infrared images","authors":"Qiong Liu, Jiajun Zhuang","doi":"10.1109/IST.2012.6295515","DOIUrl":"https://doi.org/10.1109/IST.2012.6295515","url":null,"abstract":"Designing a robust and efficient thresholding algorithm for far-infrared (FIR) images under various imaging conditions is one of critical technologies. The existing algorithms are difficult to deal with the images corrupted by noise, if a predefined filter is not used. However, it is difficult to define an appropriate filter beforehand because some prior knowledge about image noise is required. To solve this problem, an improved fast generalized fuzzy c-means (IFGFCM) is proposed to reconstruct a filtered image first regardless of the type of image noise. A novel adaptive thresholding algorithm combining IFGFCM with clustering centers analysis is then used to segment pedestrians from FIR images automatically. Experiments performed on a set of FIR images show that, compared with three other algorithms, the segmentation effectiveness of the thresholding algorithm is more consistent with the ground truth, and the resulting misclassification rate is less than 2%.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"285 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116107201","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}