{"title":"Spectral characterization of a hyperspectral imaging system using optical standards","authors":"M. Mehrubeoglu","doi":"10.1109/IST.2012.6295579","DOIUrl":"https://doi.org/10.1109/IST.2012.6295579","url":null,"abstract":"Hyperspectral imaging relies on the optical properties of materials which absorb or scatter light at different wavelengths. To obtain repeatable results from a hyperspectral or any other imaging system, the system's spectral response must be characterized using optical standards against the light source used. Light sources vary in their spectral properties and their performance over time. Differences in light sources, such as intensity or emitted wavelengths, can affect the acquired data; however, through calibration and data normalization, such effects can be minimized. Knowing the imager's spectral response to the light source is vital for analyzing hyperspectral data and interpreting the results from the media of interest. In this study, the spectral response of the hyperspectral imaging system to tungsten halogen diffuse light source is determined in reflection and transmission modes using optical standards of varying thickness. In addition, the system's response to the same light source over time is investigated. The noise levels in single and averaged spectra are measured and reported. System normalization methods are described. For the tested hyperspectral imaging system and light source, the noise reduces in averaged spectra across multiple spectra compared to single spectra. Spectral peak shifts have also been observed at different light source power levels.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"66 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":"134265013","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":"Techniques for electrical tree imaging","authors":"R. Schurch, S. Rowland, P. Withers","doi":"10.1109/IST.2012.6295555","DOIUrl":"https://doi.org/10.1109/IST.2012.6295555","url":null,"abstract":"Electrical trees are defects which can grow in polymeric electrical insulation under high electrical stresses. Their name results from their visual aspect which resembles natural trees. The growth of electrical trees is a precursor to long-term electrical failure; however, the basic mechanism of tree initiation and growth is not yet understood, and remains an important issue for high voltage engineers and equipment designers. In this paper the various techniques used for visualising electrical trees are reviewed and the key research questions concerning the mechanism of tree growth are considered. Optical techniques are mainly used, although electron microscopy adds useful information about the morphology of the defect. Most work has been focused on two-dimensional images. A novel approach using X-ray computed tomography is presented in this paper. The challenges and opportunities for the imaging community are considered. Detailed imaging of incipient trees and sub-micron detail of growth regions hold keys to the mechanisms of growth, but methods such as X-ray tomography need further enhancement to yield useful data.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"112 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":"128081804","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}
Omid Haji-Maghsoudi, Alireza Talebpour, Hamid Soltanian-Zadeh, Hossein Asl Soleimani
{"title":"Automatic informative tissue's discriminators in WCE","authors":"Omid Haji-Maghsoudi, Alireza Talebpour, Hamid Soltanian-Zadeh, Hossein Asl Soleimani","doi":"10.1109/IST.2012.6295538","DOIUrl":"https://doi.org/10.1109/IST.2012.6295538","url":null,"abstract":"Wireless capsule endoscopy (WCE) is a new device which investigates the entire gastrointestinal (GI) and especially small bowel. About 55000 frames are recorded in an examination for a capsule which captures two frames per second. Thus, it is essential to find an automatic and intelligent method to help physicians. The WCE videos have lots of uninformative parts (such as extraneous matters, bubbled, and dark part), so preprocessing is necessary to separate these uninformative regions in a frame or reduce frames' numbers. In this paper, we introduce two novel methods to detect automatically uninformative parts. In order to achieve this goal, we use two Mathematical Morphological operations, sigmoid function as a method to segment regions, statistic features, Gabor filters, fisher score test to reduce number of features, neural network and discriminators in color space. Our experimental studies indicates that precision, sensitivity, accuracy, and specificity are respectively 96.13%, 95.30%, 96.35% and 97.00% in the first method, and 90.17%, 95.68%, 93.72%, and 92.71%, respectively in the second method.","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":"116507014","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 cluster centers on building roof from LiDAR footprints","authors":"Deming Kong, Lijun Xu, Xiaolu Li, Weiwei Xing","doi":"10.1109/IST.2012.6295541","DOIUrl":"https://doi.org/10.1109/IST.2012.6295541","url":null,"abstract":"A new method for the estimation of the cluster centers on the building roof from the LiDAR footprints is proposed. The elevation image of the building roof is obtained by applying gridding method on the data of the point cloud. The distribution areas of edge lines and ridge line on the building roof are respectively extracted through the calculation of morphological gradient of the elevation image and the operation of point detection on the erosion image. By the method of Hough transform, the feature lines of the building roof are obtained from the distribution areas of them. On the basis of number and normal vectors of geometrical planes, which are composed of the feature lines, the number of the clusters and the initial values of the cluster centers on the building roof are obtained. The proposed method is validated by a simulation experiment.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"73 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":"124670301","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}
I. S. Gousias, A. Hammers, S. Counsell, A. Edwards, D. Rueckert
{"title":"Automatic segmentation of pediatric brain MRIs using a maximum probability pediatric atlas","authors":"I. S. Gousias, A. Hammers, S. Counsell, A. Edwards, D. Rueckert","doi":"10.1109/IST.2012.6295511","DOIUrl":"https://doi.org/10.1109/IST.2012.6295511","url":null,"abstract":"Automatic anatomical segmentation of pediatric brain MR data sets can be pursued with the use of registration algorithms when segmentation priors (atlases) are in hand. We investigated the performance of a maximum probability pediatric atlas (MPPA), template based registration and label propagation. The MPPA was created from the 33 pediatric data sets, available through www.brain-development.org. We evaluated the performance of the MPPA comparing with manual segmentations by means of the Dice overlap coefficient. Dice values, averaged across representative regions, were 0.90 ± 0.03 for the hippocampus, 0.92 ± 0.01 for the caudate nucleus and 0.92 ± 0.02 for the pre-central gyrus. Segmentations of 36 further unsegmented target 3T images (1-year-olds and 2-year-olds) yielded visibly high-quality results. This registration approach allows the rapid construction of automatically labeled pediatric brain atlases in a single registration step.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"7 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":"117297149","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}
M. Mehrubeoglu, Ming Yang Teng, M. Savage, A. Rafalski, P. Zimba
{"title":"Hyperspectral imaging and analysis of mixed algae species in liquid media","authors":"M. Mehrubeoglu, Ming Yang Teng, M. Savage, A. Rafalski, P. Zimba","doi":"10.1109/IST.2012.6295535","DOIUrl":"https://doi.org/10.1109/IST.2012.6295535","url":null,"abstract":"In this paper, a laboratory-based hyperspectral imaging system is used to acquire hyperspectral data cubes from different algae samples of known mixtures. The data are obtained under controlled and repeatable conditions. Hyperspectral image processing is complicated by the size of the corresponding datasets so hyperspectral image pre-processing techniques such as dimensionality reduction are necessary before spectral analysis. We assessed hyperspectral response of mixed algal cultures containing two algae types to characterize the laboratory-based hyperspectral imaging system. Changes in the hyper spectral imaging system's response to variations in volume and combinations of algae concentrations were tested. Preliminary results demonstrate the system's capability to differentiate algal species, concentrations and sample volumes.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"45 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":"116897602","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":"Demodulated resonance technique in fault diagnosis of high speed line rolling-mill synchromesh gears","authors":"Fengxing Zhou, Baokang Yan","doi":"10.1109/IST.2012.6295526","DOIUrl":"https://doi.org/10.1109/IST.2012.6295526","url":null,"abstract":"Normal vibration signal of rotating machinery is low-frequency signal, yet high-frequency component would exist when having fault, especially when the fault is caused by mechanical shock. But the shock pulse is very weak compared to the low-frequency component. Demodulated resonance technique can filter the low-frequency component and keep the high-frequency component. Then generate resonance wave in which the shock pulse is amplified. The signals from the gearbox are coupled to each other which make the fault diagnosis difficult, with multiple sources decoupling technique can detect independent signal of each measuring point. First, construct relative influence coefficient of the system, and then calculate the gain matrix. Adjust the parameters of the matrix repeatedly to eliminate the impact from other points. Finally, the amplified independent shock signal is detected through which the fault can be identified. The application approves that this method is effectively in fault diagnosis and fault location.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"95 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":"122046002","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}
Jie Wang, Longyong Chen, Xing-dong Liang, Wen Hong, Lideng Wei
{"title":"MIMO FMCW SAR system using beat-frequency division waveforms","authors":"Jie Wang, Longyong Chen, Xing-dong Liang, Wen Hong, Lideng Wei","doi":"10.1109/IST.2012.6295554","DOIUrl":"https://doi.org/10.1109/IST.2012.6295554","url":null,"abstract":"Special attention has been devoted to the lightweight, cost effective frequency modulated continuous wave (FMCW) synthetic aperture radar (SAR) in recent years. However, FMCW SAR is not feasible in the case of wider swath or higher Doppler bandwidth, because the loss of range resolution is dramatic and the system sampling rate is high. By using the technique of multi-input multi-output (MIMO), the pulse repetition frequency (PRF) of the system can be reduced dramatically without causing azimuth ambiguities. Consequently, the sweep cycle is increased, the system sampling rate is reduced, the loss of range resolution is negligible and the transmitter-receiver isolation is sufficient. The orthogonal signal transmitted in the system is beat-frequency division waveform. As the bandwidth of the beat signal is much smaller than the signal bandwidth and radio frequency (RF) carrier frequency, the difference between the transmitted signals wavelength is negligible, and the residual phase error caused by compensating phase shift can be ignored. Theoretical analysis and simulation results illustrate the feasibility of this system.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"14 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":"114075177","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":"Frequency selection for compounding synthetic aperture ultrasound images","authors":"J. R. B. Taylor, J. J. M. Chan, G. Thomas","doi":"10.1109/IST.2012.6295514","DOIUrl":"https://doi.org/10.1109/IST.2012.6295514","url":null,"abstract":"In ultrasound imaging range resolution is proportional to the bandwidth of the transmitted pulse; however, noise also increases with frequency and forces a compromise in imaging accuracy. By compounding multiple synthetic aperture ultrasound images from different frequencies, both the resolution and signal-to-noise ratio (SNR) can be improved, unlike when averaging multiple scans at a single frequency, which would only increase SNR. This paper describes a technique for frequency compounding of synthetic aperture ultrasound images and a practical test setup is introduced for frequency selection for imaging systems consisting of a single piezoelectric transducer and a variable-frequency pulser. An example is provided in which point-scatterers in water are scanned along a linear path at frequencies of 16 to 21 MHz. The resulting multi-frequency imaging increases peak SNR by 13% more than single-frequency averaging with the same number of scans and reduces the range-domain support of the point-spread function by 30%.","PeriodicalId":213330,"journal":{"name":"2012 IEEE International Conference on Imaging Systems and Techniques Proceedings","volume":"23 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":"128241621","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}
T. York, Aniediobong Jonah Ukpong, S. Mylvaganam, Yanyun Ru
{"title":"Parameter estimation from tomographic data using self-organising maps","authors":"T. York, Aniediobong Jonah Ukpong, S. Mylvaganam, Yanyun Ru","doi":"10.1109/IST.2012.6295588","DOIUrl":"https://doi.org/10.1109/IST.2012.6295588","url":null,"abstract":"The paper reports on the potential of using a type of artificial neural network, the self-organising map, for processing tomographic data from pipe separators to estimate interface levels. This is motivated by a desire to estimate process parameters without recourse to image reconstruction. Results show direct quantitative estimation of volume fraction of two-component flow mixtures containing oil and water from electrical capacitance tomography measurements. Parameter extraction from the trained feature map is realised using Gaussian mixture modelling. Parametric information of a mixture is determined by using the probability estimation of sample map and comparing the result with the model's topology. The SOM Toolbox in MATLAB was used for training and developing the models. After preparing the training data the SOM mixture model can be trained in less than 20 seconds. 75% of the two-component mixture test samples are classified within 5% of the sample's true composition.","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":"130090054","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}