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2016 IEEE International Conference on Signal and Image Processing (ICSIP)最新文献

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Multiple delayed position of echo hiding algorithm research and development 多延时位置回波隐藏算法的研究与开发
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888315
Yanmei Kang, Kaichuang Yang, J. Wang, Yueqin Liu
{"title":"Multiple delayed position of echo hiding algorithm research and development","authors":"Yanmei Kang, Kaichuang Yang, J. Wang, Yueqin Liu","doi":"10.1109/SIPROCESS.2016.7888315","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888315","url":null,"abstract":"Echo hiding algorithm is a type of Information hiding technology which has been widely used. This paper introduces the principle and the mathematical model of echo hiding algorithm. Generally, the traditional echo hiding algorithm just allows to hide 180 bits of information in 1 second, in order to increase the hiding capacity, we proposed multiple delayed position of echo hiding algorithm. It permits each segment hiding 2 bits of data and introducing 4 delay positions, we expanded echo hiding space to a double capacity. The result was tested by experiments, extracted data which was encrypted by the algorithm has a stable effect showing that this algorithm has practical value in this field.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131388799","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: 3
Fully automatic colon segmentation in computed tomography colonography 计算机断层扫描结肠镜中的全自动结肠分割
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888222
Weidong Zhang, Hyun Min Kim
{"title":"Fully automatic colon segmentation in computed tomography colonography","authors":"Weidong Zhang, Hyun Min Kim","doi":"10.1109/SIPROCESS.2016.7888222","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888222","url":null,"abstract":"Colon cancer is the second leading cause of cancer-related death in the United States, and can be prevented by the removal of precancerous colon polyps. For colon diagnosis, computed tomography colonography (CTC) has been proposed as a minimally invasive technique, and computer aided diagnosis (CAD) systems using CTC data are a rapidly evolving tool to localize, detect, and identify colon polyps. Colon segmentation is an essential and challenging step in the development of CAD systems. To accurately segment the whole colon using CTC data, we propose a fully automatic method. In this work, the whole body region excluding the lungs is first localized to narrow the search region and lower computation burden. Inside the body of the test case, a pre-trained colon atlas probability map is fitted using anatomy constraints to localize parts of the colon as seeded regions. Then, region growing is applied to generate an initial 3D segmentation. Below colon air, discriminative classifiers are used to classify regions into colon-tagged materials or non-colon regions, and a fuzzy connectedness segmentation method is applied. Combining colon air and tagged residuals, the whole colon is extracted from CTC data. Experiments were conducted on publicly available CTC database which results in better accuracy and error rate compared with other methods.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125312437","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: 2
Filtering normal papanicolaou smear with multi-instance learning 基于多实例学习的正常巴氏涂片过滤
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888234
Jie Wang, Xun Liu, Yunjie Chen, Yuan Liu, L. Pan, Huijuan Zhang, Xiang Ji, Su Zhang
{"title":"Filtering normal papanicolaou smear with multi-instance learning","authors":"Jie Wang, Xun Liu, Yunjie Chen, Yuan Liu, L. Pan, Huijuan Zhang, Xiang Ji, Su Zhang","doi":"10.1109/SIPROCESS.2016.7888234","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888234","url":null,"abstract":"Filtering normal papanicolaou smear using computer-aided system can help clinical doctors to detect cervical cancer. In this paper, we propose a scheme to classify cervical cells as normal or abnormal. The pipeline includes preprocessing, perinuclear area extraction, feature extraction and multi-instance learning (MIL). We tried and compared several feature extraction methods, including textural features, manual features and Stacked sparse autoencoder(SSAE) self-learned features. In multi-instance learning, we modify softmax classifier to be adequate for our problem besides some classic MIL algorithms. The results show that manual features or SSAE with modified softmax achieve the best performance and are recognized by clinical pathology doctors.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123180750","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
Recognition of sounds using square cauchy mixture distribution 基于方形柯西混合分布的声音识别
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888359
A. Ito
{"title":"Recognition of sounds using square cauchy mixture distribution","authors":"A. Ito","doi":"10.1109/SIPROCESS.2016.7888359","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888359","url":null,"abstract":"In this paper, a new probability density distribution, “the square Cauchy mixture distribution” is proposed for recognition of sound. The proposed density is based on the Cauchy distribution and modified so that it has mean and variance. Since the proposed density can be calculated using only simple arithmetic operations, it can be calculated faster than the Gaussian mixture model (GMM). In addition to the definition of the proposed distribution, a parameter estimation method based on the gradient descent is also described. Two experiments were conducted such as recognition of environmental sound and recognition of singer of the singing voice. The results of the experiments revealed that the proposed method was 10% to 15% faster than the GMM with addlog operation and the recognition performance was comparable.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126395158","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: 2
Digital down-conversion design based on polyphase filtering structure 基于多相滤波结构的数字下变频设计
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888337
Yingying Du, X. Ye, Yafei Li, Zhengyu Cai
{"title":"Digital down-conversion design based on polyphase filtering structure","authors":"Yingying Du, X. Ye, Yafei Li, Zhengyu Cai","doi":"10.1109/SIPROCESS.2016.7888337","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888337","url":null,"abstract":"Digital down-conversion technology based on the structure of bandpass sampling is one of the key technologies of software radio receiving system. While the traditional digital mixing orthogonal demodulation using multiplier, to a certain extent, increase the computational complexity. This paper proposes a kind of digital down-conversion design based on polyphase filtering structure, effectively reducing the computational complexity. Firstly, conducting odd-even extraction and symbol correction; secondly, using time delay filter to update; Finally, outputing baseband signal after extracting. We use of software simulation to prove its feasibility.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125282108","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: 2
Vision-based autonomous detection of lane and pedestrians 基于视觉的车道和行人自动检测
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888349
Dong-Uk Kim, Sung-Ho Park, Jong-Hee Ban, Taek-Min Lee, Y. Do
{"title":"Vision-based autonomous detection of lane and pedestrians","authors":"Dong-Uk Kim, Sung-Ho Park, Jong-Hee Ban, Taek-Min Lee, Y. Do","doi":"10.1109/SIPROCESS.2016.7888349","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888349","url":null,"abstract":"We present an efficient approach to lane and pedestrian detection by processing sequential images from a camera attached to a moving vehicle. The left and right lines of the current lane are detected by finding high intensity pixels along multiple horizontal scan lines and connecting the detected pixel points. Line positions are predicted by tracking in order to increase detection credibility while reducing processing time. Pedestrian detection is done using HOG features. Since HOG-based method is however computer intensive, an edge based adaptive method is proposed. Our approach worked well on real road scene images.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114517961","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: 3
Accurate parameter estimation of chirp class signals under low SNR 低信噪比下啁啾类信号的精确参数估计
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888295
Lin Li, Tingyu Niu, H. Ji, Hongxia Han, Yiduo Liu
{"title":"Accurate parameter estimation of chirp class signals under low SNR","authors":"Lin Li, Tingyu Niu, H. Ji, Hongxia Han, Yiduo Liu","doi":"10.1109/SIPROCESS.2016.7888295","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888295","url":null,"abstract":"Chirp signal is a common waveform in many actual information processing systems, such as speech, radar, sonar, etc. Chirp class signals include linear frequency modulation (LFM) signals and signals derived from LFM, e.g. the polyphase coded signals. In this paper, aiming at the circumstances of extremely low signal to noise ratio (SNR), we use the Lv's distribution (LVD) to represent the chirp class signals. A new parameter estimation method is proposed for polyphase coded signals based LVD. The simulations and experimental results demonstrate that the proposed method has a high accurate estimation performance for chirp class signals under low SNR.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122128968","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
Tracking loops with time-varying sampling periods for the TH-CDMA signal TH-CDMA信号的时变采样周期跟踪环路
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888314
Kai Liu, Xiye Guo, Jun Yang
{"title":"Tracking loops with time-varying sampling periods for the TH-CDMA signal","authors":"Kai Liu, Xiye Guo, Jun Yang","doi":"10.1109/SIPROCESS.2016.7888314","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888314","url":null,"abstract":"Time-hopping signal structure is adopted for overcoming the near-far problem in the Ground-based Navigation System. The signal model of TH-CDMA signal is presented. To track the pulse signals with pseudorandom active-timeslot, tracking loops with time-varying sampling periods are designed. The linear model of the second order TVSP-PLL is presented. The stability of the time-varying model is analyzed based on the First Method of Lyapunov for the linear time-varying system. A transient-response simulation of the second order TVSP-PLL is provided as a verification. The ranging performance of the TVSP-DLL is evaluated. A hardware experiment and a MATLAB simulation are used to verify the noise performance of the TVSP-DLL. The tracking loops with time varying sampling periods are implemented on the FPGA platform and MATLAB. The simulation and experiment results show that the ranging accuracy can achieve centimeter level.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116931219","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: 3
Echocardiography image enhancement using adaptive fractional order derivatives 超声心动图图像增强使用自适应分数阶导数
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888245
Ayesha Saadia, A. Rashdi
{"title":"Echocardiography image enhancement using adaptive fractional order derivatives","authors":"Ayesha Saadia, A. Rashdi","doi":"10.1109/SIPROCESS.2016.7888245","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888245","url":null,"abstract":"Medical ultrasound images are low contrast in nature. Information regarding tissues and other important structure is required by a physician to assess patient's health. Therefore image enhancement is a critical pre-processing task. In this paper a methodology based on emerging topic of fractional calculus is proposed. Proposed method is simple yet effective. In the proposed algorithm, input image is first divided into smooth, texture and edge regions using gradient magnitude of each pixel. Then appropriate order of fractional differential mask is selected to enhance each pixel. Proposed method is compared with state-of-the-art histogram equalization method and fixed-order fractional differential methods. Results are verified quantitatively and qualitatively. For quantitative analysis average gradient and entropy are used. Simulation results verify the effectiveness of proposed method.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128701081","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: 9
Automatic taxonomy induction for image collections 图像集合的自动分类归纳
2016 IEEE International Conference on Signal and Image Processing (ICSIP) Pub Date : 2016-08-01 DOI: 10.1109/SIPROCESS.2016.7888246
Yan Wu
{"title":"Automatic taxonomy induction for image collections","authors":"Yan Wu","doi":"10.1109/SIPROCESS.2016.7888246","DOIUrl":"https://doi.org/10.1109/SIPROCESS.2016.7888246","url":null,"abstract":"User annotation of images has become a popular solution for image classification and retrieval. This paper reports a machine learning approach in taxonomy induction that applies image annotations involved in different levels of meaning making from the participants. Results of the study indicate the effectiveness of the method. The study suggests that the discussed machine learning procedures can be enhanced using the proposed approach.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128946938","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
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