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2010 IEEE International Conference on Image Processing最新文献

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Multimedia forensic hash based on visual words 基于视觉词的多媒体取证哈希
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5650613
Wenjun Lu, Min Wu
{"title":"Multimedia forensic hash based on visual words","authors":"Wenjun Lu, Min Wu","doi":"10.1109/ICIP.2010.5650613","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5650613","url":null,"abstract":"In recent years, digital images and videos have become increasingly popular over the internet and bring great social impact to a wide audience. In the meanwhile, technology advancement allows people to easily alter the content of digital multimedia and brings serious concern on the trustworthiness of online multimedia information. Forensic hash is a short signature attached to an image before transmission and acts as side information for analyzing the processing history and trustworthiness of the received image. In this paper, we propose a new construction of forensic hash based on visual words representation. We encode SIFT features into a compact visual words representation for robust estimation of geometric transformations and propose a hybrid construction using both SIFT and block-based features to detect and localize image tampering. The proposed hash construction achieves more robust and accurate forensic analysis than prior work.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129872749","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: 79
Visual tracking and segmentation using Time-of-Flight sensor 基于飞行时间传感器的视觉跟踪与分割
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5652979
Omar Arif, W. Daley, P. Vela, J. Teizer, J. Stewart
{"title":"Visual tracking and segmentation using Time-of-Flight sensor","authors":"Omar Arif, W. Daley, P. Vela, J. Teizer, J. Stewart","doi":"10.1109/ICIP.2010.5652979","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5652979","url":null,"abstract":"Time-of-Flight (TOF) sensors provide range information at each pixel in addition to intensity information. They are becoming more widely available and more affordable. This paper examines the utility of dense TOF range data for image segmentation and tracking. Energy based formulations for image segmentation are used, which consist of a data term and a smoothness term. The paper proposes novel methods to incorporate range information, obtained from the TOF sensor, into the data and the smoothness term of the energy. Graph cut is used to minimize the energy.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128454031","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: 13
Detection of skin lesions using diffuse polarisation 利用漫射偏振检测皮肤病变
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5651786
Nitya Subramaniam, Gule Saman, E. Hancock
{"title":"Detection of skin lesions using diffuse polarisation","authors":"Nitya Subramaniam, Gule Saman, E. Hancock","doi":"10.1109/ICIP.2010.5651786","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5651786","url":null,"abstract":"This paper describes the use of polarisation information for surface inspection. We consider the problem of detecting regions of damage and disease in the skins of different types of fruit and vegetable. We commence by using moments to estimate the components of the polarisation image (mean-intensity, polarisation and phase) from images obtained with multiple polariser angles. Using the polarisation information and the Fresnel theory, we develop a characterisation of the surface reflectance based on spherical harmonic coefficients. We use the normalised cut method to segment surfaces into different regions depending on their surface reflectance properties. Experiments on samples of bruised fruit illustrate the practical utility of the method.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128742099","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
Monogenic-LBP: A new approach for rotation invariant texture classification 单基因- lbp:一种旋转不变纹理分类新方法
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5651885
Lin Zhang, Lei Zhang, Zhenhua Guo, David Zhang
{"title":"Monogenic-LBP: A new approach for rotation invariant texture classification","authors":"Lin Zhang, Lei Zhang, Zhenhua Guo, David Zhang","doi":"10.1109/ICIP.2010.5651885","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5651885","url":null,"abstract":"Analysis of two-dimensional textures has many potential applications in computer vision. In this paper, we investigate the problem of rotation invariant texture classification, and propose a novel texture feature extractor, namely Monogenic-LBP (M-LBP). M-LBP integrates the traditional Local Binary Pattern (LBP) operator with the other two rotation invariant measures: the local phase and the local surface type computed by the 1st-order and 2ndorder Riesz transforms, respectively. The classification is based on the image's histogram of M-LBP responses. Extensive experiments conducted on the CUReT database demonstrate the overall superiority of M-LBP over the other state-of-the-art methods evaluated.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124596455","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: 74
Semi-regular remeshing with reduced remeshing error 半规则重网格，减少重网格误差
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5653272
Leon Denis, A. Munteanu, P. Schelkens
{"title":"Semi-regular remeshing with reduced remeshing error","authors":"Leon Denis, A. Munteanu, P. Schelkens","doi":"10.1109/ICIP.2010.5653272","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5653272","url":null,"abstract":"In this paper we present a remeshing algorithm which drastically reduces the aliasing artifacts inherent in regularly-sampled remeshed objects. Starting from a semi-regular mesh, the proposed algorithm reduces the remeshing error and avoids aliasing by displacing vertices such that most samples of the original mesh are present in the remeshed model as well. Computational efficiency is provided by using a search-tree, which efficiently gathers vertices near a given point in a 3D space. Compared to the state-of-the-art semi-regular remesher, the proposed remesher drastically improves the visual quality of the high-frequency regions in remeshed objects. Additionally, the proposed algorithm yields a lower remeshing error, which is reflected by a significantly increased PSNR upper-bound in wavelet-based compression of such meshes.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129454570","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
Fast traumatic brain injury CT slice indexing via anatomical feature classification 基于解剖特征分型的颅脑损伤CT快速分型
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5652317
Ruizhe Liu, Shimiao Li, C. Tan, B. Pang, C. Lim, C. Lee, Qi Tian, Zhuo Zhang
{"title":"Fast traumatic brain injury CT slice indexing via anatomical feature classification","authors":"Ruizhe Liu, Shimiao Li, C. Tan, B. Pang, C. Lim, C. Lee, Qi Tian, Zhuo Zhang","doi":"10.1109/ICIP.2010.5652317","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5652317","url":null,"abstract":"Computed tomography (CT) is used widely in traumatic brain injury diagnosis. One axial brain CT scan consists of multiple slices with different heights along the brain axial direction. Indexing of brain CT slices is to order the slices and align each individual slice onto the corresponding brain axial height, which is an important step in content-based image retrieval and computer-assisted diagnosis. Current existing methods for this indexing task are through the image registration techniques by registering 2D image slices onto a 3D brain atlas. In this paper, instead of using the registration methods, we propose a fast indexing method using anatomical feature classification. In our method, the brain CT scan is divided into 6 height levels along the axial direction so that slices in each level share similar anatomical structure. In this way, the indexing problem becomes a classification problem that one series of scan slices are to be classified into 6 classes. Experimental results show that the proposed method is effective and efficient.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129477029","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
Histogram of confidences for person detection 人检测的置信直方图
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5649809
L. Middleton, James R. Snowdon
{"title":"Histogram of confidences for person detection","authors":"L. Middleton, James R. Snowdon","doi":"10.1109/ICIP.2010.5649809","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5649809","url":null,"abstract":"This paper focuses on the problem of person detection in harsh industrial environments. Different image regions often have different requirements for the person to be detected. Additionally, as the environment can change on a frame to frame basis even previously detected people can fail to be found. In our work we adapt a previously trained classifier to improve its performance in the industrial environment. The classifier output is initially used an image descriptor. Structure from the descriptor history is learned using semi-supervised learning to boost overall performance. In comparison with two state of the art person detectors we see gains of 10%. Our approach is generally applicable to pretrained classifiers which can then be specialised for a specific scene.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130498251","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
Cone-restricted kernel subspace methods 锥限制核子空间方法
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5653014
Takumi Kobayashi, F. Yoshikawa, N. Otsu
{"title":"Cone-restricted kernel subspace methods","authors":"Takumi Kobayashi, F. Yoshikawa, N. Otsu","doi":"10.1109/ICIP.2010.5653014","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5653014","url":null,"abstract":"We propose cone-restricted kernel subspace methods for pattern classification. A cone is mathematically defined in a manner similar to a linear subspace with a nonnegativity constraint. Since the angles between vectors (i.e., inner products) are fundamental to the cone, kernel tricks can be directly applied. The proposed methods approximate the distribution of sample patterns by using the cone in kernel feature space via kernel tricks, and the classification is more accurate than that of the kernel subspace method. Due to the nonlinearity of kernel functions, even a single cone in the kernel feature space can can cope with multi-modal distributions in the original input space. In the experimental results on person detection and motion detection, the proposed methods exhibit the favorable performances.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126980625","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
Color exploitation in hog-based traffic sign detection 基于hog的交通标志检测中的色彩开发
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5651637
Ivo M. Creusen, R. Wijnhoven, E. Herbschleb, P. D. With
{"title":"Color exploitation in hog-based traffic sign detection","authors":"Ivo M. Creusen, R. Wijnhoven, E. Herbschleb, P. D. With","doi":"10.1109/ICIP.2010.5651637","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5651637","url":null,"abstract":"We study traffic sign detection on a challenging large-scale real-world dataset of panoramic images. The core processing is based on the Histogram of Oriented Gradients (HOG) algorithm which is extended by incorporating color information in the feature vector. The choice of the color space has a large influence on the performance, where we have found that the CIELab and YCbCr color spaces give the best results. The use of color significantly improves the detection performance. We compare the performance of a specific and HOG algorithm, and show that HOG outperforms the specific algorithm by up to tens of percents in most cases. In addition, we propose a new iterative SVM training paradigm to deal with the large variation in background appearance. This reduces memory consumption and increases utilization of background information.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129107980","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: 136
Robust reconstruction of arbitrarily deformed bokeh from ordinary multiple differently focused images 从普通多张不同聚焦图像中实现任意变形散景的鲁棒重建
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5650900
K. Kodama, Ippeita Izawa, Akira Kubota
{"title":"Robust reconstruction of arbitrarily deformed bokeh from ordinary multiple differently focused images","authors":"K. Kodama, Ippeita Izawa, Akira Kubota","doi":"10.1109/ICIP.2010.5650900","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5650900","url":null,"abstract":"This paper deals with a method of generating seriously deformed bokeh on reconstructed images from ordinary multiple differently focused images including just simple bokeh such as Gaussian blurs. We previously proposed scene re-focusing with various iris shapes by applying a three-dimensional filter to the multi-focus images. However, actually the proposed method implicitly assumed that the feature of the iris can be expressed mathematically and it has some symmetry like a horizontally open iris. In this paper, at first, the captured multi-focus images are robustly decomposed into components, each of which goes through its own corresponding pin-hole on the lens, by using dimension reduction and a two-dimensional filter. Then, based on the appropriate composition of the components, reconstruction of arbitrarily deformed bokeh introduced by any user-defined iris is achieved. By some experiments, we show that our novel method can generate even seriously deformed bokeh that does not have simple symmetry.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129208748","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
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