{"title":"Miniature system for chronic neural recording in pigeons and small animals","authors":"Xiaofeng Liu, Xianqiang Yang, Feng Guo, Yuan Shi","doi":"10.1109/IST.2009.5071674","DOIUrl":"https://doi.org/10.1109/IST.2009.5071674","url":null,"abstract":"With the extraordinary navigational ability in large-scale space, homing pigeons have been a valuable model to investigate the neurophysiological substrate of large-scale spatial cognition. Here we show a miniature chronic recording system that can be mounted on the back of freely behaving pigeons. In this paper, we mainly focus on the design and implementation of the headstage comprised of an instrument amplifier with high input impedance and stable gain, which allows multi-unit recording from a pair of electrodes implanted in the brain of pigeons. We also briefly introduce the backpack components and discuss the further optimal design of the system.","PeriodicalId":373922,"journal":{"name":"2009 IEEE International Workshop on Imaging Systems and Techniques","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125248055","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}
Zhou Qian, Ma Jianshe, Zhang Song, Guo Hongfeng, C. Xuemin
{"title":"A location tracking method based on reflection image detection used in interactive projector-camera system","authors":"Zhou Qian, Ma Jianshe, Zhang Song, Guo Hongfeng, C. Xuemin","doi":"10.1109/IST.2009.5071633","DOIUrl":"https://doi.org/10.1109/IST.2009.5071633","url":null,"abstract":"with the great advantages of interactive projection technology, the new optical-electronic human-computer interactive large screen display system has been paid more and more attention. In this paper, the approach with a new optical structure based on linear detectors has been presented. This system consists of computer, projector, camera and digital pen, and the camera uses two linear detectors to detect the infrared light point, which is reflected by two stripe mirrors separately, so that the location of the light point could be measured. This method has the advantages of anti-obstruct, fast tracking, low-cost, and can be widely used in teaching, training, and so on.","PeriodicalId":373922,"journal":{"name":"2009 IEEE International Workshop on Imaging Systems and Techniques","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126776903","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}
G. Papakostas, Dimitrios Alexios Karras, Basil G. Mertzios
{"title":"Dealing with peaks overlapping issue in quantifying metabolites in MRSI","authors":"G. Papakostas, Dimitrios Alexios Karras, Basil G. Mertzios","doi":"10.1109/IST.2009.5071602","DOIUrl":"https://doi.org/10.1109/IST.2009.5071602","url":null,"abstract":"A novel methodology deals with the peaks overlapping issue in quantifying metabolites in MRSI is proposed in this paper. The introduced method encounters the metabolites quantification procedure as a typical optimization problem able to be solved by using optimization methods of the computational intelligence. A simple genetic algorithm is applied in order to find the metabolites peaks parameters that best match the spectrum in process. This novel approach comes to overcome the disadvantages of the neural networks, used for the same purpose, where the overlapping issue is handled difficultly. The experimental results are very promising showing that highly overlapped metabolites peaks can quantified accurately, by using the proposed method and place the basis for further investigation.","PeriodicalId":373922,"journal":{"name":"2009 IEEE International Workshop on Imaging Systems and Techniques","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122841950","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}
Wei Rao, Jing-jing Lian, Fei Xia, Li Fan, Hui-jun Xu, Wen-qun Tan, Guo-xing Dai
{"title":"Simple approach for joint blind equalization and order detection suitable for QAM signal","authors":"Wei Rao, Jing-jing Lian, Fei Xia, Li Fan, Hui-jun Xu, Wen-qun Tan, Guo-xing Dai","doi":"10.1109/IST.2009.5071662","DOIUrl":"https://doi.org/10.1109/IST.2009.5071662","url":null,"abstract":"A blind equalization and order detection algorithm suitable for QAM signal is proposed. By exploiting the inherent structural relationship between the 4-QAM signal's coordinates and other higher-order QAM signals' coordinates, a novel cost function including channel blind equalization and signal order detection is defined. In such method, by changing the coordinates of input signals, higher-order QAM signal can be equalized by the statistics of 4-QAM and its order can be detected accurately. Examples of five modulation types - 4-QAM, 8-QAM, 16-QAM, 32-QAM and 64-QAM - are given. Simulation results show that the proposed algorithm achieves satisfactory performance.","PeriodicalId":373922,"journal":{"name":"2009 IEEE International Workshop on Imaging Systems and Techniques","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126213096","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}
N. Zhang, Q. Liao, S. Ruan, S. Lebonvallet, Yuemin Zhu
{"title":"Multi-kernel SVM based classification for tumor segmentation by fusion of MRI images","authors":"N. Zhang, Q. Liao, S. Ruan, S. Lebonvallet, Yuemin Zhu","doi":"10.1109/IST.2009.5071605","DOIUrl":"https://doi.org/10.1109/IST.2009.5071605","url":null,"abstract":"Tumor segmentation, a significant application in the field of medical imaging and pattern recognition, is still a very difficult and unsolved problem up to now. In this paper, an improved SVM algorithm—multi-kernel SVM, integrated with data fusion process, is proposed to segment the tumors from the MRI image sequence. Three kinds of MRI image sequence-T2, PD, FLAIR are used as input sources in learning and classifying process. Then a region growing step is exploited for a refinement of the tumor contour. At last, according to the follow-up result of the same patient at five different periods, it is obvious that the tumor's volume becomes smaller, and an evaluation percentage is given to prove the effectiveness of the therapy. The quantification of result demonstrates the effectiveness of the proposed method.","PeriodicalId":373922,"journal":{"name":"2009 IEEE International Workshop on Imaging Systems and Techniques","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128044154","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":"Statictics of Gabor features for coin recognition","authors":"L. Shen, Sen Jia, Z. Ji, Wen-Sheng Chen","doi":"10.1109/IST.2009.5071653","DOIUrl":"https://doi.org/10.1109/IST.2009.5071653","url":null,"abstract":"We present an image based approach for coin classification. Gabor wavelets are used to extract features for local texture representation. To achieve rotation-invariance, concentric ring structure is used to divide the coin image into a number of small sections. Statistics of Gabor coefficients within each section is then concatenated into a feature vector for whole image representation. Matching between two coin images are done via Euclidean distance measurement and the nearest neighbor classifier. The public MUSCLE database consisting of over 10,000 images is used to test our algorithm, results show that significant improvements over edge distance based methods have been achieved.","PeriodicalId":373922,"journal":{"name":"2009 IEEE International Workshop on Imaging Systems and Techniques","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134550141","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":"Indirect real-time measurement of the penpoint in an interactive projector-camera system","authors":"Hongfeng Guo, Jianshe Ma, Qian Zhou, Song Zhang, Xirong Lin, Xuemin Cheng","doi":"10.1109/IST.2009.5071635","DOIUrl":"https://doi.org/10.1109/IST.2009.5071635","url":null,"abstract":"Real-time interactive on documents can enhance effectiveness of learning in modern education. A pen capable of locating on a screen is one significant choice. Some products have been developed and the nib of pen is used as the emitter. However, the pen might fail to be located while our body or hand would block the light wherever the photo detector is. In this paper, we have proposed a scheme to solve the problem. It will detect the nib of pen indirectly. Meanwhile, for the realization of real time, we choose PSD(position sensitive detector) as the detector to track the light of the LEDs. And by using the method of coding, multiple light points detected by one PSD could be achieved.","PeriodicalId":373922,"journal":{"name":"2009 IEEE International Workshop on Imaging Systems and Techniques","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134560863","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":"Mitigation of atmospheric contrast degradation via image enhancement","authors":"J. Oakley","doi":"10.1109/IST.2009.5071606","DOIUrl":"https://doi.org/10.1109/IST.2009.5071606","url":null,"abstract":"Images obtained in bad weather such as haze, fog may have low contrast, particularly towards the top of the image. The technical challenge is to reverse this process - provided with just the “foggy” scene, estimate the contribution due to optical scattering and so recover the original scene. This is possible for a general flat-field scene and a forward-looking camera, although there are some limitations due to noise effects.","PeriodicalId":373922,"journal":{"name":"2009 IEEE International Workshop on Imaging Systems and Techniques","volume":"309 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131802501","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":"Gas-water two-phase flow regime identification with feature fusion from an ERT system and a V-cone meter","authors":"C. Tan, F. Dong","doi":"10.1109/IST.2009.5071655","DOIUrl":"https://doi.org/10.1109/IST.2009.5071655","url":null,"abstract":"Gas-water two-phase flow is of significance in industrial process and scientific research field. Its flow regime determines the flow parameters and the method of flow measurement. Precise identification of flow regime has been a popular subject for a long time. In this work, a series of experiments on gas-water two-phase flows were conducted in a 50mm diameter horizontal pipe, the flow parameters were measured with an Electrical Resistance Tomography (ERT) system and a V-cone meter. A method of feature extraction from the above two instruments is presented and the flow regime was recognized by using a Support Vector Machine (SVM) method. Additionally, the feature fusion methods are selected and compared to discuss the method of improving the flow regime recognition performance.","PeriodicalId":373922,"journal":{"name":"2009 IEEE International Workshop on Imaging Systems and Techniques","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128932193","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":"Iterative and single-step solutions of multi-offset ultra wide band data in the time domain","authors":"S. Binajjaj, T. Zanoon, Mohd Zaid Abdullah","doi":"10.1109/IST.2009.5071658","DOIUrl":"https://doi.org/10.1109/IST.2009.5071658","url":null,"abstract":"This paper deals with the inverse scattering of ultra wide band (UWB) tomography used in reconstruction the dialectic properties of the unknown targets in 2D. The image reconstruction algorithm is based on the gradient minimization of an augmented cost function defined as the different between measured and calculated fields. The computation requires two successive steps: (i) direct and (ii) adjoint solutions. The forward-backward time stepping algorithm, implementing the finite-difference time-domain (FDTD) method with Mur's absorbing boundaries is employed in both steps. The imaging algorithm is based on non-linear optimization technique from which the single-step and iterative inversion schemes are derived. The experimental results demonstrate that the algorithms can resolve features whose sizes are comparable to the half wave-length even though scaterring data are collected only from limited view angles. These experimental evidence suggest that the technique could potentially be used to solve practical imaging problems such as detecting cancerous tumors in breast.","PeriodicalId":373922,"journal":{"name":"2009 IEEE International Workshop on Imaging Systems and Techniques","volume":"293 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132816781","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}