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2017 2nd International Conference on Multimedia and Image Processing (ICMIP)最新文献

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Night Image Enhancement Using Selective Filters 夜间图像增强使用选择性过滤器
2017 2nd International Conference on Multimedia and Image Processing (ICMIP) Pub Date : 2017-03-01 DOI: 10.1109/ICMIP.2017.41
M. Sodanil, Siranee Nuchitprasitchai, Chalermpong Intarat
{"title":"Night Image Enhancement Using Selective Filters","authors":"M. Sodanil, Siranee Nuchitprasitchai, Chalermpong Intarat","doi":"10.1109/ICMIP.2017.41","DOIUrl":"https://doi.org/10.1109/ICMIP.2017.41","url":null,"abstract":"In this paper, we propose the technique of image enhancement to improve the quality of the outdoor night video from the video surveillance system. The sub-image homomorphic filtering technique is applied for using selective filters. The process started by dividing video clip into images frames, then separating into both horizontal and vertical parts before enhancing with homomorphic filtering method. Furthermore, the scene information of outdoor night video and the highlight details are recovered. The data source video was recorded only in the night time. The results show that the HMMOD method with BBRF is given an average of PSNR equal to 29.6227 dB, NC equal to 0.9961 and BNRF given average of PSNR equal to 22.5129 dB, NC equal to 0.9910, compared with the original images from ten outdoor videos at night. Therefore, the experiment shows that the proposed method can be used to improve the performance of video surveillance system in terms of PNSR and NC.","PeriodicalId":227455,"journal":{"name":"2017 2nd International Conference on Multimedia and Image Processing (ICMIP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131245836","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
A Zero-Watermarking Method to Protect Intellectual Property under Strong Geometric Attacks 强几何攻击下知识产权保护的零水印方法
2017 2nd International Conference on Multimedia and Image Processing (ICMIP) Pub Date : 2017-03-01 DOI: 10.1109/ICMIP.2017.43
Liu Tian
{"title":"A Zero-Watermarking Method to Protect Intellectual Property under Strong Geometric Attacks","authors":"Liu Tian","doi":"10.1109/ICMIP.2017.43","DOIUrl":"https://doi.org/10.1109/ICMIP.2017.43","url":null,"abstract":"Watermarking is an important technical way to realize copyright protection of intellectual property. The traditional video watermarking can cause distortion to host video in a certain extent, and has a weak robustness against strong geometric attacks. Firstly, a Nonnegative Matrix Factorization with Sparseness Constraints on Parts (NMFSCP) method is proposed in this paper. Secondly, the NMFSCP is utilized to obtain coefficient matrix with geometric invariance. Finally, the coefficient matrix is used to generate robust zero-watermarking. The experiments indicate that, the proposed zero-watermarking not only can resist conventional video signal processing such as adding noise and filtering, etc., but also shows strong robustness against strong geometric attacks such as rotation, scaling, translation, and cropping, etc., and moreover, can play the role in copyright protection of intellectual property without causing any visual perceptible distortion.","PeriodicalId":227455,"journal":{"name":"2017 2nd International Conference on Multimedia and Image Processing (ICMIP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134046314","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
Robotic-Assisted Respiration-Corrected 4D Ultrasound Imaging for Image-Guided Interventions 用于图像引导干预的机器人辅助呼吸校正4D超声成像
2017 2nd International Conference on Multimedia and Image Processing (ICMIP) Pub Date : 2017-03-01 DOI: 10.1109/ICMIP.2017.48
Jiaze Wu, Qian Yan, Jing Ye, Xinsheng Yuan, Jimin Liu
{"title":"Robotic-Assisted Respiration-Corrected 4D Ultrasound Imaging for Image-Guided Interventions","authors":"Jiaze Wu, Qian Yan, Jing Ye, Xinsheng Yuan, Jimin Liu","doi":"10.1109/ICMIP.2017.48","DOIUrl":"https://doi.org/10.1109/ICMIP.2017.48","url":null,"abstract":"Widely used freehand 3D ultrasound systems do not provide corrections to effectively track breathing-induced moving organs. In this paper, a novel 4D ultrasound imaging method is proposed to create a sequence of breathing-corrected 3D ultrasound images from multiple 2D US image sequences, which is acquired by using a robotic arm to hold a 2D US probe and tilt it to regularly scan the liver. An image-based method is introduced to label the respiratory phases of the acquired images. Based on the extracted phases, the acquired 2D images are then resampled to reconstruct a sequence of respiration-corrected 3D ultrasound images. The reconstructed 3D images can capture the moving 3D liver during half a breathing cycle. Initial experiments demonstrate that the proposed method is feasible to visualize the 3D liver motion.","PeriodicalId":227455,"journal":{"name":"2017 2nd International Conference on Multimedia and Image Processing (ICMIP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114205324","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
Biometrics Encryption Based on Palmprint and Convolutional Code 基于掌纹和卷积码的生物特征加密
2017 2nd International Conference on Multimedia and Image Processing (ICMIP) Pub Date : 2017-03-01 DOI: 10.1109/ICMIP.2017.33
Jian Qiu, Hengjian Li, Jiwen Dong, Guang Feng
{"title":"Biometrics Encryption Based on Palmprint and Convolutional Code","authors":"Jian Qiu, Hengjian Li, Jiwen Dong, Guang Feng","doi":"10.1109/ICMIP.2017.33","DOIUrl":"https://doi.org/10.1109/ICMIP.2017.33","url":null,"abstract":"Based on palmprint and convolutional code, a biometrics encryption method is proposed. Firstly, the period of randomly generated keys are extended. It is then encoded with our convolutional code to get what we call a pseudo-palm code. It will be locked by XORing it with the user¡¯s reference palmprint features code. The above two aspects of processing information is stored in the smart card. During the decoding phase, the user presents his palmprint features to unlock the key. After XORing with the date on the smart card, it is then decoded with convolutional code and voted to get original keys. The scheme adopts biometrics encryption method with palmprint and convolutional code, which is more secure than single password authentication, and is more accurate than single biometric authentication.","PeriodicalId":227455,"journal":{"name":"2017 2nd International Conference on Multimedia and Image Processing (ICMIP)","volume":"2008 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127316833","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
A Novel Method for Improving Artifacts of Chinese Calligraphy Character Skeleton Extraction 一种改进中国书法文字骨架提取器物的新方法
2017 2nd International Conference on Multimedia and Image Processing (ICMIP) Pub Date : 2017-03-01 DOI: 10.1109/ICMIP.2017.38
Jiulong Zhang, Xia’ni Wang, Ligang Zhang, Su Yang, Qing Zhao
{"title":"A Novel Method for Improving Artifacts of Chinese Calligraphy Character Skeleton Extraction","authors":"Jiulong Zhang, Xia’ni Wang, Ligang Zhang, Su Yang, Qing Zhao","doi":"10.1109/ICMIP.2017.38","DOIUrl":"https://doi.org/10.1109/ICMIP.2017.38","url":null,"abstract":"Chinese calligraphy style evaluation and generation are important to the aim of cultural heritage preservation. Character skeleton extraction is a key preprocessing step and most existing algorithms suffer from drawbacks of non-single pixel width, bifurcation etc. In this paper, an optimization process is proposed to overcome these drawbacks to some extent. It gets the provisional skeleton using a rotation invariant thinning algorithm, and proposes a two-step process to further optimize the results: a) to reduce the skeleton to single pixel in width, and b) a maximum circle method to merge the bifurcation points. Experimental results on several databases show that the proposed approach obtains better skeletons than existing benchmarking methods.","PeriodicalId":227455,"journal":{"name":"2017 2nd International Conference on Multimedia and Image Processing (ICMIP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126223781","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
A New Collaborative Filtering Algorithm Based on Data Smoothing 一种新的基于数据平滑的协同过滤算法
2017 2nd International Conference on Multimedia and Image Processing (ICMIP) Pub Date : 2017-03-01 DOI: 10.1109/ICMIP.2017.29
Li Ma, Xingjun Wang, Anqi Chen, Riqiang Gao, Yuanyuan Tang, Linghao Xiao
{"title":"A New Collaborative Filtering Algorithm Based on Data Smoothing","authors":"Li Ma, Xingjun Wang, Anqi Chen, Riqiang Gao, Yuanyuan Tang, Linghao Xiao","doi":"10.1109/ICMIP.2017.29","DOIUrl":"https://doi.org/10.1109/ICMIP.2017.29","url":null,"abstract":"Based on the advantages of data smoothing, this paper presents a new collaborative filtering algorithm to solve the problem of data sparsity in recommender system. The key innovation of the algorithm consists of clustering and data smoothing. Clustering is used to find out the similarity between users. This paper adopts a new method to cluster users. Data smoothing is designed to solve the problem of data sparsity. It smooths data by introducing Pearson Correlation Coefficient. Then selecting items through nearest neighbor algorithm. Finally, it gets the preference matrix by weighting preference of items. Compared with another typical collaborative filtering algorithm on precision, recall and F1, the new approach performs better.","PeriodicalId":227455,"journal":{"name":"2017 2nd International Conference on Multimedia and Image Processing (ICMIP)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114938896","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
A Hybrid Deep Learning Approach for Texture Analysis 纹理分析的混合深度学习方法
2017 2nd International Conference on Multimedia and Image Processing (ICMIP) Pub Date : 2017-01-08 DOI: 10.1109/ICMIP.2017.5
Hussein Adly, Mohamed N. Moustafa
{"title":"A Hybrid Deep Learning Approach for Texture Analysis","authors":"Hussein Adly, Mohamed N. Moustafa","doi":"10.1109/ICMIP.2017.5","DOIUrl":"https://doi.org/10.1109/ICMIP.2017.5","url":null,"abstract":"Texture classification is a problem that has variousapplications such as remote sensing and forest speciesrecogni- tion. Solutions tend to be custom fit to the datasetused but fails to generalize. The Convolutional NeuralNetwork (CNN) in combination with Support Vector Machine(SVM) form a robust selection between powerful invariantfeature extractor and accurate classifier. The fusion ofexperts provides stability in classification rates amongdifferent datasets.","PeriodicalId":227455,"journal":{"name":"2017 2nd International Conference on Multimedia and Image Processing (ICMIP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132780899","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
Automatic Visual Theme Discovery from Joint Image and Text Corpora 基于图像和文本联合语料库的视觉主题自动发现
2017 2nd International Conference on Multimedia and Image Processing (ICMIP) Pub Date : 2016-09-07 DOI: 10.1109/ICMIP.2017.3
Ke Sun, Xianxu Hou, Qian Zhang, G. Qiu
{"title":"Automatic Visual Theme Discovery from Joint Image and Text Corpora","authors":"Ke Sun, Xianxu Hou, Qian Zhang, G. Qiu","doi":"10.1109/ICMIP.2017.3","DOIUrl":"https://doi.org/10.1109/ICMIP.2017.3","url":null,"abstract":"This paper presents an unsupervised visual theme discovery framework as a better (more compact and effective) alternative for semantic representation of visual contents. Firstly, a tag filtering algorithm was proposed focusing on the tag’s ability of visual content description. Then a spectral clustering algorithm is applied to cluster tags into visual themes based on their visual similarity and semantic similarity measures. User studies have been conducted to evaluate the effectiveness and rationality of the discovered visual themes and obtain promising results. Additionally, two common computer vision tasks, example based image search and keyword based image search to explore potential applications of the proposed framework. The experimental results show that visual themes significantly outperform tags on semantic image understanding and achieve state-of-art performance inthese two tasks.","PeriodicalId":227455,"journal":{"name":"2017 2nd International Conference on Multimedia and Image Processing (ICMIP)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124077191","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
Vison-Based Traffic Flow Prediction Using Dynamic Texture Model and Gaussian Process 基于视觉的动态纹理模型和高斯过程交通流预测
2017 2nd International Conference on Multimedia and Image Processing (ICMIP) Pub Date : 2016-07-14 DOI: 10.1109/ICMIP.2017.20
Bin Liu, Hao Ji, Yi Dai
{"title":"Vison-Based Traffic Flow Prediction Using Dynamic Texture Model and Gaussian Process","authors":"Bin Liu, Hao Ji, Yi Dai","doi":"10.1109/ICMIP.2017.20","DOIUrl":"https://doi.org/10.1109/ICMIP.2017.20","url":null,"abstract":"In this paper, a work in progress towards a real-time vision-based traffic flow prediction (TFP) system is resented. The proposed method consists of three elemental operators, that are dynamic texture model based motion segmentation, feature extraction and Gaussian process (GP) regression. The objective of motion segmentation is to recognize the target regions covering the moving vehicles in the sequence of visual processes. The feature extraction operator aims to extract useful features from the target regions. The extracted features are then mapped to the number of vehicles through the operator of GP regression. A training stage using historical visual data is required for determining the parameter values of the GP. Based on a low-resolution visual data set, preliminary evaluations on the performance of the proposed method are performed. The results show that the proposed method beats a benchmark solution based on Gaussian mixture model, and has the potential to be developed into qualified and practical solutions to real-time TFP.","PeriodicalId":227455,"journal":{"name":"2017 2nd International Conference on Multimedia and Image Processing (ICMIP)","volume":"331 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117063981","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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