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Iris segmentation for non-cooperative recognition systems

IET IMAGE PROCESSING 2011年第5期5卷 448-456页

作者： Chen, R. Lin, X. R. Ding, T. H. Tsinghua Univ Grad Sch Shenzhen Shenzhen 518055 Peoples R China Tsinghua Univ State Key Lab Precis Measurement Technol & Instru Beijing 100084 Peoples R China

Segmenting iris texture from an input image is an important step for recognising iris pattern. It is still a difficult task to localise available texture regions from non-ideal iris images captured in non-cooperative situations such as lighting variations, on-the-move and off-angle view. To address this problem, this study presents a novel algorithm for accurate and fast iris segmentation. An adaptive mean shift procedure is built to find the rough position of the iris centre. According to the localisation result, a circle is set as the initial iris contour. After combining the statistical texture prior modelled as Markov random field, a merged active contour model is established in terms of level set theory. Under the MAC model, the initial contour is iteratively driven to real iris boundaries. During the curve evolving process, eyelids, eyelashes, reflections and shadows can be simultaneously detected and labelled in iris regions. The novelty of the proposed method mainly includes developing a new modified mean shift procedure for fast and robust iris localisation, and successfully incorporating the local probabilistic prior, boundary and region information into the designed active contour model for accurate texture segmentation. Extensive experimental results on various challenging iris images show that our method can effectively and accurately perform iris segmentation with low computational complexity and has very promising applications in non-cooperative recognition systems.

关键词： iris texture segmentation probability eyelids statistical analysis mean shift procedure off-angle view accurate texture segmentation adaptive mean shift procedure lighting variations eyelashes on-the-move view curve evolving process Image recognition statistical texture prior modeling iris recognition active contour model iris pattern recognition robust iris localisation computer vision and image processing techniques reflections image segmentation noncooperative recognition systems iris contour Markov random field image texture computational complexity MAC model Markov processes level set theory Other topics in statistics

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Local binary patterns and its variants for face recognition

Local binary patterns and its variants for face recognition

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International Conference on Recent Trends in Information Technology

作者： Meena, K. Suruliandi, A. Department of Computer Science and Engineering Sardar Raja College of Engineering Tirunelveli India Department of Computer Science and Engineering Manonmaniam Sundaranar University Tirunelveli India

ISBN: (纸本)9781457705885

Face recognition is one of the most important tasks in computer vision and Biometrics. Texture is an important spatial feature useful for identifying objects or regions of interest in an image. Texture based face recognition is widely used in many applications. LBP method is most successful for face recognition. It is based on characterizing the local image texture by local texture patterns. In this paper performance evaluation of Local Binary pattern (LBP) and its modified models Multivariate Local Binary pattern (MLBP), Center Symmetric Local Binary pattern (CS-LBP) and Local Binary pattern Variance (LBPV) are investigated. Facial features are extracted and compared using K nearest neighbour classification algorithm. G-statistics distance measure is used for classification. Experiments were conducted on JAFFE female, CMU-PIE and FRGC version 2 databases. The results shows that CS-LBP consistently performs much better than the remaining other models. © 2011 IEEE.

关键词： Local binary pattern

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A new dataset of Persian handwritten documents and its segmentation

A new dataset of Persian handwritten documents and its segme...

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2011 7th Iranian Conference on Machine vision and Image Processing, MVIP 2011

作者： Alaei, Alireza Nagabhushan, P. Pal, Umapada Department of Studies in Computer Science University of Mysore Mysore 570006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India

ISBN: (纸本)9781457715358

In document image analysis and especially in handwritten document image recognition, standard datasets play vital roles for evaluating performances of algorithms and comparing results obtained by different groups of researchers. In this paper, an unconstrained Persian handwritten text dataset (PHTD) is introduced. The PHTD contains 140 handwritten documents of three different categories written by 40 individuals. Total number of text-lines and words/subwords in the dataset are 1787 and 27073, respectively. In most of the PHTD documents either an overlapping or a touching text-lines is present. The average number of text-lines in documents of the PHTD is 13. Two types of ground truths based on pixels information and content information are generated for the dataset. Providing these two types of ground truths for the PHTD, it can be utilized in many areas of document image processing such as sentence recognition/understanding, text-line segmentation, word segmentation, word recognition, and character segmentation. To provide a framework for other researches, recent text-line segmentation results on this dataset are also reported. © 2011 IEEE.

关键词： Image segmentation

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vision algorithms for automated census of animals

Vision algorithms for automated census of animals

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2011 IEEE Applied Imagery pattern recognition Workshop: Imaging for Decision Making, AIPR 2011

作者： Cohen, Charles J. Haanpaa, Doug Rowe, Steve Zott, James P. Cybernet Systems Corporation Ann Arbor MI United States Environmental Management Edwards Air Force Base CA United States

ISBN: (纸本)9781467302159

Numerous military bases have a requirement, based on the Sikes Act, to maintain the base's natural environment while still meeting military mission objectives. One method used to accomplish this is by working toward the goal of achieving habitat and species sustainability. One difficulty is that there is currently no adequate baseline of the ecosystem;specifically, a critical need is the detection, identification, and tracking of animals on Federal and State endangered lists 24 hours a day. For instance, the U.S. Fish and Wildlife Service lists 130 animals as either endangered or threatened, including the desert tortoise, the Mohave ground squirrel, various species of fox, jaguar, mountain beaver, and wolf. In order to even begin to form an appropriate natural environmental baseline, the location and movements of these animals must be acquired, recorded, and made available for review. © 2011 IEEE.

关键词： computer vision

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Automatic Search of Nursing Diagnoses

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16th Iberoamerican Congress on pattern recognition

作者： Morales, Matias A. Figueroa, Rosa L. Cabrera, Jael E. Univ Concepcion Dept Elect Engn Concepcion Chile Guillermo Grant Benavente Hosp Dept Cardiac Surg Cardiac Surg ICU Region del Bio Bio Chile

ISBN: (纸本)9783642250842

Nursing documentation is all the information that nurses register regarding the clinical assessment and care of a patient. Currently, these records are manually written in a narrative style;consequently, their quality and completeness largely depends on the nurse's expertise. This paper presents an algorithm based on standardized nursing language that searches and sorts nursing diagnoses by its relevance through a ranking. Diagnoses identification is performed by searching and matching patterns among a set of patient needs or symptoms and the international standard of nursing diagnoses NANDA. Three sorting methods were evaluated using 6 utility cases. The results suggest that TF-IDF (83.43% accuracy) and assignment of weights by hit (80.73% accuracy) are the two best alternatives to implement the ranking of diagnoses.

关键词： NANDA Nursing documentation pattern Matching Diagnosis retrieval Decision Support TF TF-IDF

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Simultaneous dimensionality reduction and human age estimation via kernel partial least squares regression

Simultaneous dimensionality reduction and human age estimati...

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作者： Guo, Guodong Mu, Guowang West Virginia University Lane Dept. of CSEE Morgantown WV United States Hebei University of Technology School of Science Tianjin China

ISBN: (纸本)9781457703942

Human age estimation has recently become an active research topic in computer vision and pattern recognition, because of many potential applications in reality. In this paper we propose to use the kernel partial least squares (KPLS) regression for age estimation. The KPLS (or linear PLS) method has several advantages over previous approaches: (1) the KPLS can reduce feature dimensionality and learn the aging function simultaneously in a single learning framework, instead of performing each task separately using different techniques;(2) the KPLS can find a small number of latent variables, e.g., 20, to project thousands of features into a very low-dimensional subspace, which may have great impact on real-time applications;and (3) the KPLS regression has an output vector that can contain multiple labels, so that several related problems, e.g., age estimation, gender classification, and ethnicity estimation can be solved altogether. This is the first time that the kernel PLS method is introduced and applied to solve a regression problem in computer vision with high accuracy. Experimental results on a very large database show that the KPLS is significantly better than the popular SVM method, and outperform the state-of-the-art approaches in human age estimation. © 2011 IEEE.

关键词： computer vision

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Medical Image Computing and computer-Assisted Intervention - MICCAI 2011 2011

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丛书名： Lecture Notes in computer Science

2011年

作者： Gabor Fichtinger Anne Martel Terry Peters

ISBN: (数字)9783642236266

ISBN: (纸本)9783642236259

The three-volume set LNCS 6891, 6892 and 6893 constitutes the refereed proceedings of the 14th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2011, held in Toronto, Canada, in September 2011. Based on rigorous peer reviews, the program committee carefully selected 251 revised papers from 819 submissions for presentation in three volumes. The third volume includes 82 papers organized in topical sections on computer-aided diagnosis and machine learning, and segmentation.

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Distributed multi-camera visual mapping using topological maps of planar regions

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pattern recognition 2011年第7期44卷 1528-1539页

作者： Montijano, Eduardo Sagues, Carlos Univ Zaragoza Dept Informat & Ingn Sistemas I3A E-50009 Zaragoza Spain

This paper presents a multi-agent solution for cooperative visual mapping using planar regions. Each agent is assumed to be equipped with a conventional camera and has limited communication capabilities. Our approach starts building topological maps from independent image sequences where natural landmarks extracted from conventional images are grouped to create a graph of planes. With this approach the features observed in several images belonging to the same planar region are stored only once, reducing the size of the individual maps. In a distributed scenario this is very important because smaller maps can be transmitted faster, which makes our approach better suited for cooperative mapping. The later fusion of the individual maps is obtained via distributed consensus without any initial information about the relations between the different maps. Experiments with real images in complex scenarios show the good performance of our proposal. (c) 2011 Elsevier Ltd. All rights reserved.

关键词： computer vision Distributed systems Mapping

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Modelling imprints of pharmaceutical tablets for imprint quality visual inspection

Modelling imprints of pharmaceutical tablets for imprint qua...

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2011 International Conference on Image Processing, computer vision, and pattern recognition, IPCV 2011

作者： Možina, Miha Tomaževič, Dejan Pernuš, Franjo Likar, Boštjan Sensum Computer Vision Systems Tehnološki Park 21 1000 Ljubljana Slovenia University of Ljubljana Faculty of Electrical Engineering Laboratory of Imaging Technologies Tržaška 25 1000 Ljubljana Slovenia

ISBN: (纸本)9781601321916

Identification of pharmaceutical tablets plays a key role in preventing mix-ups among various types of tablets. Since identification of tablets is most frequently done by imprints, good imprint quality, a property that makes the imprint readable, is of utmost importance. In this paper, we propose a novel method for automated visual inspection of tablets for defect detection and imprint quality inspection. Performance of the method was evaluated on a real tablet image database of imprinted tablets. A "gold standard" was established by manually classifying the tablets into good and defective class. The ROC (receiver operating characteristics) analysis indicated that the proposed method yields better sensitivity and specificity than the previous defect detection method.

关键词： Inspection

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Improved support vectors for classification through preserving neighborhood geometric structure constraint

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OPTICAL ENGINEERING 2011年第8期50卷

作者： Wang, Xuchu Niu, Yanmin Chongqing Univ Minist Educ Key Lab Optoelect Technol & Syst Chongqing 400044 Peoples R China Chongqing Normal Univ Coll Comp & Informat Sci Chongqing 400050 Peoples R China

The support vector machine (SVM) has become a popular classifier in pattern recognition, computer vision, and other fields. Traditional SVM may result in a nonrobust solution for classifying complex data because its separating hyperplane only reflects the marginal distance information of isolated support vectors, while discarding some useful class structural information. In this paper a new support vector classifier with neighborhood preserving constraint is proposed to enhance the support vectors by preserving the local geometric structure on the manifold of within-class samples. This structure can be represented as a weighted graph matrix and regulated by adding a preprocessing transform in standard SVM. Experimental results validate its effectiveness with comparison to related methods on several synthetic and real-world data sets and show its competence, especially for classifying high dimensional data in a small sample size case. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3610982]

关键词： pattern classification support vector machine manifold learning locally linear embedding neighborhood preserving embedding small sample size problem

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