检索结果-内蒙古大学图书馆

International Conference on Frontiers in Handwriting Recognition

作者： Chanda, Sukalpa Franke, Katrin Pal, Umapada Dept. of Computer Science and Media Technology Gjøvik University College Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

ISBN: (纸本)9780769542218

Arbitrary orientation and sparse data content are common characteristics of torn document. To ensure accuracy and reliability in computer-based analysis, content-zone segmentation is required. In our previous work, we studied segmentation of handwritten and printed text. A questioned document-piece in the form of an office note, however, might also contain non-text data like logos, graphics, and pictures. Hence a more precise content-zone classification is required. In this paper we propose a two-Tier approach for non-text, handwriting and printed text segmentation. The first Tier aims to discriminate text and non-text regions. The second Tier classifies handwritten and printed text within all text zones identified during the first Tier. Gabor features and chain-code features are used in Tier-1 and Tier-2, respectively. By using SVM classifier we successfully identified 97.65% of 31,227 text regions in our current test data. The proposed approach identified 98.69% of printed and 96.39% of handwritten text amongst all identified text regions. © 2010 IEEE.

关键词： Text processing

来源：评论

学校读者我要写书评

暂无评论

An efficient algorithm for detection of road-like structures in satellite images

An efficient algorithm for detection of road-like structures...

引用

13th International Conference on pattern Recognition, ICPR 1996

作者： Mukherjee, A. Parui, S.K. Chaudhuri, D. Chaudhuri, B.B. Krishnan, R. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Calcutta India Advanced Data Processing Research Institute Secunderabad India

ISBN: (纸本)081867282X

Road networks are important features of satellite imagery. The main contribution of the present road detection method consists of an effective enhancement technique and an efficient segmentation technique that removes non-road pixels step by step from the image where parameters involved: in each step images are determined by the sensor characteristics (like spatial resolution and spectral range) of the satellite. Also, the segmentation process depends not only on the road contrast but also on the road length. Thus, a low contrast but long road segment does not get removed. We have tested the algorithm on a number of images from IRS and SPOT satellites and the results are satisfactory. © 1996 IEEE.

关键词： Satellite imagery

来源：评论

学校读者我要写书评

暂无评论

Semi-supervised multi-feature learning for person re-identification

Semi-supervised multi-feature learning for person re-identif...

引用

2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2013

作者： Figueira, Dario Bazzani, Loris Minh, Ha Quang Cristani, Marco Bernardino, Alexandre Murino, Vittorio Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy ISR Instituto Superior Técnico Lisboa Portugal

ISBN: (纸本)9781479907038

Person re-identification is probably the open challenge for low-level video surveillance in the presence of a camera network with non-overlapped fields of view. A large number of direct approaches has emerged in the last five years, often proposing novel visual features specifically designed to highlight the most discriminant aspects of people, which are invariant to pose, scale and illumination. On the other hand, learning-based methods are usually based on simpler features, and are trained on pairs of cameras to discriminate between individuals. In this paper, we present a method that joins these two ideas: given an arbitrary state-of-the-art set of features, no matter their number, dimensionality or descriptor, the proposed multi-class learning approach learns how to fuse them, ensuring that the features agree on the classification result. The approach consists of a semi-supervised multi-feature learning strategy, that requires at least a single image per person as training data. To validate our approach, we present results on different datasets, using several heterogeneous features, that set a new level of performance in the person re-identification problem. © 2013 IEEE.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

On minimizing errors in 3D reconstruction for stereo camera systems

引用

pattern Recognition and Image Analysis 2007年第2期17卷 337-348页

作者： Wenhardt, S. Denzler, J. Niemann, H. Department of Pattern Recognition University of Erlangen-Nurnberg Martensstr. 3 91058 Erlangen Germany Department of Computer Vision Friedrich Schiller University of Jena Ernst-Abbe-Platz 2 07743 Jena Germany

Active reconstruction of 3D surfaces deals with the control of camer a viewpoints to minimize error and uncertainty in the reconstructed shape of an object. In this paper we develop a mathematical relationship between the setup and focal lengths of a stereo camera system and the corresponding error in 3D reconstruction of a given surface. We explicitly model the noise in the image plane, which can be interpreted as pixel noise or as uncertainty in the localization of corresponding point features. The results can be used to plan sensor positioning, e.g., using information theoretic concepts for optimal sensor data selection. © Nauka/Interperiodica 2007.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Geometric image labeling with global convex labeling constraints 11th

Geometric image labeling with global convex labeling constra...

引用

11th International Conference on Energy Minimization Methods in computer vision and pattern Recognition, EMMVCPR 2017

作者： Zern, Artjom Rohr, Karl Schnörr, Christoph Image and Pattern Analysis Group Heidelberg University Heidelberg Germany Biomedical Computer Vision Group BIOQUANT Heidelberg University Heidelberg Germany

ISBN: (纸本)9783319781983

In [2], a smooth geometric labeling approach was introduced by following the Riemannian gradient flow of a given objective function on the so-called assignment manifold. The approach evaluates a user-defined data term and performs spatial regularization by Riemannian averaging of the assignment vectors. In this paper, we extend this approach in order to impose global convex constraints on the labeling results based on linear filter statistics in the label space. The smoothness of the approach is preserved by using logarithmic barrier functions to handle the new constraints. We discuss how suitable filters can be determined from example data of a given image class, and we demonstrate numerically the effectiveness of the constraints in several academic labeling scenarios. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Geometry

来源：评论

学校读者我要写书评

暂无评论

Segmentation of Bangla handwritten text into characters by recursive contour following 5

Segmentation of Bangla handwritten text into characters by r...

引用

5th International Conference on Document Analysis and Recognition, ICDAR 1999

作者： Bishnu, A. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Calcutta700035 India

ISBN: (纸本)0769503187

Segmentation of handwritten words into characters is one of the important components in handwritten text OCR. In this paper we put forward a method for the segmentation of handwritten Bangla (an Indo-Bangladeshi language) text into characters. Based on certain characteristics of Bangla writing methods, different zones across the height of the word are detected. These zones provide certain structural information about the constituent characters of the respective word. In Bangla handwritten texts often there is overlap between rectangular hulls of successive characters. As such the characters are seldom vertically separable. So, we propose a method of recursive contour following in one of the zones across the height of the word to find out the extents within which the main portion of the character lies. If the successive characters are not touching in the zone of contour following, the algorithm gives fairly good results. © 1999 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fisher kernels for handwritten word-spotting

Fisher kernels for handwritten word-spotting

引用

ICDAR2009 - 10th International Conference on Document Analysis and Recognition

作者： Perronnin, Florent Rodriguez-Serrano, Jose A. Textual and Visual Pattern Analysis Xerox Research Centre Europe France Computer Vision Centre Universitat Autonoma de Barcelona Spain

ISBN: (纸本)9780769537252

The Fisher kernel is a generic framework which combines the benefits of generative and discriminative approaches to pattern classification. In this contribution, we propose to apply this framework to handwritten word-spotting. Given a word image and a keyword generative model, the idea is to generate a vector which describes how the parameters of the keyword model should be modified to best fit the word image. This vector can then be used as the input of a discriminative classifier. We compare the performance of the proposed approach with that of a generative baseline on a challenging real-world dataset of customer letters. When the kernel used by the classifier is linear, the performance improvement is marginal but the proposed system is approximately 15 times faster than the baseline. If we use a non-linear kernel devised for this task, we obtain a 15% relative reduction of the error but the detector is approximately 15 times slower. © 2009 IEEE.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Kernel-based classification for brain connectivity graphs on the Riemannian manifold of positive definite matrices 12

Kernel-based classification for brain connectivity graphs on...

引用

12th IEEE International Symposium on Biomedical Imaging, ISBI 2015

作者： Dodero, Luca Minh, Ha Quang Biagio, Marco San Murino, Vittorio Sona, Diego Pattern Analysis and Computer Vision Istituto Italiano di Tecnologia Genova Italy NeuroInformatics Laboratory Fondazione Bruno Kessler Trento Italy

ISBN: (纸本)9781479923748

An important task in connectomics studies is the classification of connectivity graphs coming from healthy and pathological subjects. In this paper, we propose a mathematical framework based on Riemannian geometry and kernel methods that can be applied to connectivity matrices for the classification task. We tested our approach using different real datasets of functional and structural connectivity, evaluating different metrics to describe the similarity between graphs. The empirical results obtained clearly show the superior performance of our approach compared with baseline methods, demonstrating the advantages of our manifold framework and its potential for other applications. © 2015 IEEE.

关键词： Geometry

来源：评论

学校读者我要写书评

暂无评论

CNN based common approach to handwritten character recognition of multiple scripts 13

CNN based common approach to handwritten character recogniti...

引用

13th International Conference on Document Analysis and Recognition, ICDAR 2015

作者： Maitra, Durjoy Sen Bhattacharya, Ujjwal Parui, Swapan K. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata-108 India

ISBN: (纸本)9781479918058

There are many scripts in the world, several of which are used by hundreds of millions of people. Handwritten character recognition studies of several of these scripts are found in the literature. Different hand-crafted feature sets have been used in these recognition studies. However, convolutional neural network (CNN) has recently been used as an efficient unsupervised feature vector extractor. Although such a network can be used as a unified framework for both feature extraction and classification, it is more efficient as a feature extractor than as a classifier. In the present study, we performed certain amount of training of a 5-layer CNN for a moderately large class character recognition problem. We used this CNN trained for a larger class recognition problem towards feature extraction of samples of several smaller class recognition problems. In each case, a distinct Support Vector Machine (SVM) was used as the corresponding classifier. In particular, the CNN of the present study is trained using samples of a standard 50-class Bangla basic character database and features have been extracted for 5 different 10-class numeral recognition problems of English, Devanagari, Bangla, Telugu and Oriya each of which is an official Indian script. Recognition accuracies are comparable with the state-of-the-art. © 2015 IEEE.

关键词： Character recognition

来源：评论

学校读者我要写书评

暂无评论

Multi-spectral scale and rotation invariant associative memory method for pattern recognition

Multi-spectral scale and rotation invariant associative memo...

引用

Optics, Illumination, and Image Sensing for Machine vision III 1988

作者： Kimball, Steven F. Messner, Richard A. University of New Hampshire Synthetic Vision and Pattern Analysis Laboratory Department of Electrical and Computer Engineering DurhamNH03824 United States

The method of using log-polar mapping with spectral band separation to form feature vectors for an associative memory is investigated. Log-polar mapping is used to provide the scale and rotation invariant properties. This reduces the teaching time and total capacity requirement for the associative memory because all orientations and sizes of the target object need not be learned. The images are also broken down into spatial frequency bands. The use of this technique is motivated by evidence that similar processes occur in the human visual system. Suspected benefits include enhanced recognition in the presence of noise and improved network robustness. Simulation results are presented for the case of character recognition. © 1989 SPIE. All rights reserved.

关键词： Associative processing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：