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IEEE International Workshop on Information Forensics and Security (WIFS)

作者： Nitin Khanna Edward J. Delp Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

Recently there has been a great deal of interest using features intrinsic to a data-generating sensor for the purpose of source identification. Numerous methods have been proposed for different problems related to digital image forensics. The goal of our work is to identify the scanner used for generating a scanned (digital) version of a printed (hard-copy) document. In this paper we describe the use of texture analysis to identify the scanner used to scan a text document. The efficacy of our proposed method is also demonstrated.

关键词： Scanner forensics Document forensics

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User generated video annotation using Geo-tagged image databases

User generated video annotation using Geo-tagged image datab...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Golnaz Abdollahian Edward J. Delp Video and Image Processing Laboratory (VIPER) School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

In this paper we propose a system that annotates a user generated video based on the associated location metadata, by exploiting user-tagged image databases. An example of such a database is a photo sharing Web site such as Flickr where users upload their images and annotate them with various tags. The goal is to find the tags that have high probability of being relevant to the video without any complex object or action recognition being done to the video sequence. A video is first segmented into camera views and a set of keyframes are selected to represent the video. We will describe the concept of camera view as the basic element of user generated videos which has special properties suitable for the video annotation application. The keyframes are used to retrieve the most relevant images in the database. A ldquotag processingrdquo step is then used to tag the video.

关键词： image databases Video sharing Cameras Video sequences image segmentation Supervised learning Motion analysis image processing Laboratories Data engineering

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Perceptual quality evaluation for texture and motion based video coding

Perceptual quality evaluation for texture and motion based v...

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IEEE International Conference on image processing

作者： Marc Bosch Fengqing Zhu Edward J. Delp Video and Image Processing Laboratory VIPER School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

One approach that can be used to increase compression efficiency beyond the data rates achievable by state-of-the-art video codecs is to use content-based methods whereby not all the pixels are conventionally encoded. An approach to reduce the data rate is to use different coding methods for pixels belonging to areas containing large amount of detail that are costly to encode, for example textures. This can be extended by focusing on the semantic meaning of objects represented in the video sequence and also taking into consideration human visual system properties. The goal is to determine where ¿detail-irrelevant¿ regions are located in the frame and synthesize them with acceptable perceptual quality. In this paper, we discuss the effects and trade-offs of these techniques based on a set of perceptual experiments and analyze how these areas can influence the viewer's attention.

关键词： Video coding image coding Pixel Video sequences Humans Video codecs Visual system image reconstruction Quality assessment Video compression

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Development and evaluation of text localization techniques based on structural texture features and neural classifiers

Development and evaluation of text localization techniques b...

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ICDAR2009 - 10th International Conference on Document Analysis and Recognition

作者： Emmanouilidis, Christos Batsalas, Costas Papamarkos, Nikos Computational Systems Unit CETI/R.C.ATHENA 58 Tsimiski St. Xanthi 67100 Greece Image Processing and Multimedia Laboratory Dept. of Electrical and Computer Engineering Democritus Univ. of Thrace Xanthi 67100 Greece

ISBN: (纸本)9780769537252

This paper presents a text localization approach for binarized printed document images. Emphasis is given to the feature extraction and feature selection stages. In the former, several document structure elements and spatial features, likely to convey useful information, are extracted. In the latter, evolutionary multiobjective feature selection is employed to identify combinations of features with simultaneous good performance in terms of text localization sensitivity and specificity. The selected features are applied to a range of classifiers. Performance results over document image sets from known databases are presented, employing the classifiers with or without feature selection. The results suggest that the hybrid techniques, which utilize the classifiers in combination with the customized pre-processing, feature extraction and feature selection stages, exhibit promising performance on a range of document images. © 2009 IEEE.

关键词： Feature Selection

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Spectral derivative feature coding for hyperspectral signature analysis

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Pattern Recognition 2009年第3期42卷 395-408页

作者： Chang, Chein-I Chakravarty, Sumit Chen, Hsian-Min Ouyang, Yen-Chieh Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Environmental Restoration and Disaster Reduction Research Center National Chung Hsing University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Department of Radiology China Medical University Hospital Taichung Taiwan

This paper presents a new approach to hyperspectral signature analysis, called spectral derivative feature coding (SDFC). It is derived from texture features used in texture classification to dictate gradient changes among adjacent bands in characterizing spectral variations so as to improve better spectral discrimination and classification. In order to evaluate its performance, two known binary coding methods, spectral analysis manager (SPAM) and spectral feature-based binary coding (SFBC) are used to conduct comparative analysis. Experimental results demonstrate that the proposed SDFC performs more effectively in capturing spectral characteristics than do SPAM and SFBC. © 2008 Elsevier Ltd. All rights reserved.

关键词： Spectrum analysis

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A variational framework for 3D colonic polyp visualization in virtual colonoscopy

A variational framework for 3D colonic polyp visualization i...

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IEEE International Conference on image processing

作者： Dongqing Chen Aly A. Farag Robert L. Falk Gerald W. Dryden Computer Vision & Image Processing (CVIP) Laboratory Department of Electrical and Computer Engineering University of Louisville Louisville KY USA Jewish Hospital Louisville KY USA Division of Gastroenterology/Hepatology University of Louisville Louisville KY USA

Colorectal cancer includes cancer of the colon, rectum, anus and appendix. Since it is largely preventable, it is extremely important to detect and treat the colorectal cancer in the earliest stage. Virtual colonoscopy is an emerging screening technique for colon cancer. One component of virtual colonoscopy, image pre-processing, is important for colonic polyp detection/ diagnosis, feature extraction and classification. This paper introduces a general variational approach based framework for a computer aided diagnosis system for colorectal cancer. It includes techniques for 3D colon segmentation, 3D colon object reconstruction by iso-surface generation, and 3D centerline extraction. The proposed framework has been validated on 22 real CT colonography datasets.

关键词： Colonic polyps Visualization Virtual colonoscopy Cancer Colon Colonography image segmentation Optical computing Computed tomography image reconstruction

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Real-time processing of simplex growing algorithm

Real-time processing of simplex growing algorithm

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2009 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2009

作者： Wu, Chao-Cheng Chang, Chein-I. Ren, Husen Chang, Yang Lang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Center for Space and Remote Sensing Research National Central University Jhong-Li Tao-Yuan Taiwan Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9781424433957

Simplex growing algorithm (SGA) was recently developed as an alternative to the N-finder algorithm (N-FINDR) which is shown to be a promising endmember extraction technique. This paper further extends the SGA to a real-time processing algorithm, referred to as real-time SGA (RT SGA) that can effectively address four major issues arising in practical implementation for N-FINDR, (1) use of random initial endmembers which causes inconsistent final results, (2) very high computational complexity which results from an exhaustive search for finding all endmembers simultaneously, (3) requirement of dimensionality reduction because of enormous data volumes to be processed and (4) lack of real-time capability. ©2009 IEEE.

关键词： Extraction

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Fetal R-wave detection from multichannel abdominal ECG recordings in low SNR

Fetal R-wave detection from multichannel abdominal ECG recor...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Shahrzad Kharabian Mohammad B. Shamsollahi Reza Sameni Biomedical Signal and Image Processing Laboratory (BiSIPL) School of Electrical Engineering Sharif University of Technology Tehran Iran School of Electrical & Computer Engineering Shiraz University Shiraz Iran

Abdominal recordings of fetal ECG (fECG) have lower signal-to-noise ratio (SNR) as compared with invasive procedures. In this paper we have combined two previously proposed methods, one for extracting fECG, called piCA and the other, a transformation based on Hilbert transform to enhance the R-peaks. The combination of these methods seems to work well in situations of noisy data and fetal repositioning. Also a comparison is done by using ICA in order to extract the fetal signals. Performance of both methods is studied separately. Results show that applying the transformation on the components extracted with the use of piCA (after maternal ECG cancellation), had a very good performance. Also, as piCA ranks the components according to their resemblance to maternal ECG, it could be used in automatic fetal ECG extraction algorithms.

关键词： Abdomen Electrocardiography Signal processing algorithms Fetal heart Data mining Independent component analysis Magnetic recording Interference Magnetic separation Electrodes

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Fingerprint Feature Compression Using Statistical Coding Techniques

Fingerprint Feature Compression Using Statistical Coding Tec...

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IEEE India Conference (INDICON)

作者： C. Saravanan Sanjeev S. Malalur Micahel T. Manry Computer Centre National Institute of Technology Durgapur West Bengal India Department of Electrical Engineering Image Processing & Neural Networks Laboratory University of Technology Arlington USA

ISBN: (纸本)9781424448586;9781424448593

We have proposed a new fingerprint feature compression scheme, which extracts the fingerprint feature using pseudo-spectral fusion approach and compresses the fingerprint feature using statistical coding technique. The compression scheme starts with fingerprint image acquisition, enhancement, and normalization. Further, the direction and density of the fingerprint image are extracted. Fusing these two direction and density data results finger print feature data. The fingerprint feature data is applied directly using a statistical coding technique to get compressed data. The Huffman coding and arithmetic coding is used for compression and found arithmetic coding performs better. This proposed compression scheme achieves nearly 85% compression rate, which is higher compared to other present techniques achieved 45% to 63% compression.

关键词： Fingerprint recognition image coding image matching Multiresolution analysis Arithmetic Neural networks Data mining Feature extraction Huffman coding Discrete wavelet transforms

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Segmentation and registration based analysis of microscopy images

Segmentation and registration based analysis of microscopy i...

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IEEE International Conference on image processing

作者： Kevin S. Lorenz Francisco Serrano Paul Salama Edward J. Delp Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN USA School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN USA

Optical microscopy exhibits many challenges for digital image analysis. In general, microscopy volumes are inherently anisotropic, suffer from decreasing contrast with tissue depth, and characteristically have low signal levels. This paper describes a method to segment multiphoton fluorescent microscopy images via a combination of segmentation and registration methods. In particular, the proposed method utilizes image enhancement and spatial filtering along with registration and temporal filtering. Experimental results demonstrate the efficacy of the proposed method.

关键词： image segmentation image analysis Optical microscopy Filtering Geometrical optics Optical filters Digital images Anisotropic magnetoresistance Fluorescence image enhancement

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