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Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)最新文献

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A hierarchical image authentication watermark with improved localization and security 一种改进了定位和安全性的分层图像认证水印
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958538
M. Celik, Gaurav Sharma, E. Saber, A. Tekalp
{"title":"A hierarchical image authentication watermark with improved localization and security","authors":"M. Celik, Gaurav Sharma, E. Saber, A. Tekalp","doi":"10.1109/ICIP.2001.958538","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958538","url":null,"abstract":"Several fragile watermarking schemes presented in the literature are either vulnerable to vector quantization (VQ) counterfeiting attacks or sacrifice localization accuracy to improve security. Using a hierarchical structure, we propose a method that thwarts the VQ attack while sustaining the superior localization properties of blockwise independent watermarking methods. In particular, we propose dividing the image into blocks in a multi-level hierarchy and calculating block signatures in this hierarchy. While signatures of small blocks on the lowest level of the hierarchy ensure superior accuracy of tamper localization, higher level block signatures provide increasing resistance to VQ attacks. At the top level, a signature calculated using the whole image completely thwarts the counterfeiting attack. Moreover, \"sliding window\" searches through the hierarchy enable the verification of untampered regions after an image has been cropped.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"10 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120996995","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: 62
Optical flow estimation using high frame rate sequences 基于高帧率序列的光流估计
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958646
Sukhwan Lim, A. Gamal
{"title":"Optical flow estimation using high frame rate sequences","authors":"Sukhwan Lim, A. Gamal","doi":"10.1109/ICIP.2001.958646","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958646","url":null,"abstract":"Gradient-based optical flow estimation methods such as the Lucas-Kanade (1981) method work well for scenes with small displacements but fail when objects move with large displacements. Hierarchical matching-based methods do not suffer from large displacements but are less accurate. By utilizing the high speed imaging capability of CMOS image sensors, the frame rate can be increased to obtain more accurate optical flow with wide range of scene velocities in real time. Further, by integrating the memory and processing with the sensor on the same chip, optical flow estimation using high frame rate sequences can be performed without unduly increasing the off-chip data rate. The paper describes a method for obtaining high accuracy optical flow at a standard frame rate using high frame rate sequences. The Lucas-Kanade method is used to obtain optical flow estimates at high frame rate, which are then accumulated and refined to obtain optical flow estimates at a standard frame rate. The method is tested on video sequences synthetically generated by perspective warping. The results demonstrate significant improvements in optical flow estimation accuracy with moderate memory and computational power requirements.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127199151","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: 50
Optimum detection of robust perceptual-model-based image-adaptive watermarks 基于感知模型的鲁棒图像自适应水印的优化检测
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958535
Qiang Cheng, Thomas S. Huang
{"title":"Optimum detection of robust perceptual-model-based image-adaptive watermarks","authors":"Qiang Cheng, Thomas S. Huang","doi":"10.1109/ICIP.2001.958535","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958535","url":null,"abstract":"Image-adaptive watermarking based on sophisticated human perceptual models is capable of embedding watermarks with maximum strengths while incurring no perceptual loss. Very strong robustness as well as high information capacity can be achieved using these schemes. In this paper, the optimum detector for the perceptual-model-based robust watermarking is constructed, and the performance analysis is investigated. The new detector asymptotically is most efficient for weak signals, and particularly it is the most powerful for the perceptual-model-constrained watermarks. The experiments results validate our theoretical analysis.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127214034","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
Combining support vector machines for accurate face detection 结合支持向量机进行准确的人脸检测
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.959230
I. Buciu, Constantine Kotropoulos, I. Pitas
{"title":"Combining support vector machines for accurate face detection","authors":"I. Buciu, Constantine Kotropoulos, I. Pitas","doi":"10.1109/ICIP.2001.959230","DOIUrl":"https://doi.org/10.1109/ICIP.2001.959230","url":null,"abstract":"The paper proposes the application of majority voting on the output of several support vector machines in order to select the most suitable learning machine for frontal face detection. The first experimental results indicate a significant reduction of the rate of false positive patterns.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127286212","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: 32
Solarspire: querying temporal solar imagery by content Solarspire:按内容查询时间太阳图像
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.959175
Matthew L. Hill, Vittorio Castelli, Chung-Sheng Li, Yuan-Chi Chang, L. Bergman, John R. Smith, B. Thompson
{"title":"Solarspire: querying temporal solar imagery by content","authors":"Matthew L. Hill, Vittorio Castelli, Chung-Sheng Li, Yuan-Chi Chang, L. Bergman, John R. Smith, B. Thompson","doi":"10.1109/ICIP.2001.959175","DOIUrl":"https://doi.org/10.1109/ICIP.2001.959175","url":null,"abstract":"In this paper, we describe a novel content-based retrieval application which permits astrophysicists to search large image sequence archives for solar phenomenon, such as solar flares, based on the spatio-temporal behavior of the solar phenomenon. Specifically, images are preprocessed to identify bright and dark spots based on their relative intensity with respect to their neighboring regions. Temporally persistent objects are then extracted from the collection of spots, and their spatio-temporal behavior represented as intensity and size time series. Users define a query in terms of a model of spatio-temporal behaviors through a Web-based interface. The stored intensity and size time series are searched, and series segments that match the specified specified spatio-temporal behavior are returned. The benchmark results based on 2500 satellite images show that the proposed methodology demonstrated better than 85% accuracy on a solar phenomenon previously identified by astrophysicists.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127457659","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: 14
Vector quantization for image compression using circular structured self-organization feature map 基于圆形结构自组织特征映射的矢量量化图像压缩
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958523
T. Yamamoto
{"title":"Vector quantization for image compression using circular structured self-organization feature map","authors":"T. Yamamoto","doi":"10.1109/ICIP.2001.958523","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958523","url":null,"abstract":"We propose a stable and robust vector quantization coding scheme for image compression known as circular self organization feature map (CSOM) by introducing circular structure to a basic codebook. This structure enables the self organization feature map (SOM) method to converge faster, and to learn input vectors more efficiently. The results suggest that CSOM gains approximately 30% speedup in computation time and 0.3 dB in the PSNR compared to the conventional SOM algorithm. In addition, robustness for initial state of a codebook is achieved by CSOM.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127521174","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
Medical image segmentation and retrieval via deformable models 基于可变形模型的医学图像分割与检索
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958312
Lifeng Liu, S. Sclaroff
{"title":"Medical image segmentation and retrieval via deformable models","authors":"Lifeng Liu, S. Sclaroff","doi":"10.1109/ICIP.2001.958312","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958312","url":null,"abstract":"A new method based on deformable shape models for medical image segmentation is described. Experiments for blood cell micrographs have been conducted to verify the accuracy of the shape model-based segmentation and object shape description method. The cell segmentation method does not require user input for initialization. Coherence information between cells is utilized via a globally consistent cost function. The proposed segmentation method can be used in automated analysis for images of stained blood smear and segmentation of other medical structures. A method for shape population-based retrieval is also described. Results of population-based image queries for a database of blood cell micrographs are shown.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124919283","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
Face recognition using fractal codes 基于分形代码的人脸识别
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958050
H. Ebrahimpour-Komleh, V. Chandran, S. Sridharan
{"title":"Face recognition using fractal codes","authors":"H. Ebrahimpour-Komleh, V. Chandran, S. Sridharan","doi":"10.1109/ICIP.2001.958050","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958050","url":null,"abstract":"In this paper we propose a new method for face recognition using fractal codes. Fractal codes represent local contractive, affine transformations which when iteratively applied to range-domain pairs in an arbitrary initial image result in a fixed point close to a given image. The transformation parameters such as brightness offset, contrast factor, orientation and the address of the corresponding domain for each range are used directly as features in our method. Features of an unknown face image are compared with those pre-computed for images in a database. There is no need to iterate, use fractal neighbor distances or fractal dimensions for comparison in the proposed method. This method is robust to scale change, frame size change and rotations as well as to some noise, facial expressions and blur distortion in the image.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126050226","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: 52
A floating gate CMOS Euclidean distance calculator and its application to hand-written digit recognition 浮栅CMOS欧氏距离计算器及其在手写数字识别中的应用
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.958123
S. Vlassis, G. Fikos, S. Siskos
{"title":"A floating gate CMOS Euclidean distance calculator and its application to hand-written digit recognition","authors":"S. Vlassis, G. Fikos, S. Siskos","doi":"10.1109/ICIP.2001.958123","DOIUrl":"https://doi.org/10.1109/ICIP.2001.958123","url":null,"abstract":"In this work, a Euclidean distance calculator is presented. The circuit comprises of simple computing blocks, their basic element being the floating gate MOSFET (FGMOS), exploiting the merits of this device in designing circuits with low-voltage and rail-to-rail operation. Therefore the overall circuit has the characteristics of modularity, low-voltage and rail-to-rail operation under a single supply voltage, accuracy and simplicity. The circuit is designed with 2/spl mu/ MIETEC CMOS technology and is used in the simulation of a hand-written digit recognition system using the nearest neighbour classification method. The simulation results presented, demonstrate the functionality of the circuit.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123412638","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: 7
Unsupervised classification using spatial region growing segmentation and fuzzy training 基于空间区域增长分割和模糊训练的无监督分类
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205) Pub Date : 2001-10-07 DOI: 10.1109/ICIP.2001.959159
Sanghoon Lee, M. Crawford
{"title":"Unsupervised classification using spatial region growing segmentation and fuzzy training","authors":"Sanghoon Lee, M. Crawford","doi":"10.1109/ICIP.2001.959159","DOIUrl":"https://doi.org/10.1109/ICIP.2001.959159","url":null,"abstract":"This study has presented an approach to unsupervisedly estimate the number of classes and the parameters of defining the classes in order to train the classifier. Region growing segmentation and local fuzzy classification have been employed to find the sample classes that well represent the true image. The segmentation algorithm makes use of spatial contextual information in a hierarchical clustering procedure and multi-window operation using a pyramid-like structure to increase the computational efficiency. The fuzzy classification, which conducts classification by iteratively identifying expected maximum likelihood parameters of the class, is applied for the segmented regions in order to determine the sample classes. The maximum likelihood classifier has been used the unlabelled regions to assign them into one of a finite number of classes. The algorithm has been evaluated with simulated image data with various class patterns.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123707824","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
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