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Handwritten Numeral recognition of Six Popular Indian Scripts

Handwritten Numeral Recognition of Six Popular Indian Script...

引用

International Conference on Document Analysis and recognition

作者： U. Pal N. Sharma T. Wakabayashi F. Kimura Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Tsu Japan

ISBN: (纸本)9780769528229;0769528228

India is a multi-lingual multi-script country but there is not much work towards handwritten character recognition of Indian languages. In this paper we propose a modified quadratic classifier based scheme towards the recognition of off-line handwritten numerals of six popular Indian scripts. Here we consider Devnagari, Bangla, Telugu, Oriya, Kannada and Tamil scripts for our experiment. The features used in the classifier are obtained from the directional information of the numerals. For feature computation, the bounding box of a numeral is segmented into blocks and the directional features are computed in each of the blocks. These blocks are then down sampled by a Gaussian filter and the features obtained from the down sampled blocks are fed to a modified quadratic classifier for recognition. Here we have used two sets of feature. We have used 64 dimensional features for high-speed recognition and 400 dimensional features for high-accuracy recognition in our proposed system. A five-fold cross validation technique has been used for result computation and we obtained 99.56%, 98.99%, 99.37%, 98.40%, 98.71% and 98.51% accuracy from Devnagari, Bangla, Telugu, Oriya, Kannada, and Tamil scripts, respectively.

关键词： Handwriting recognition Natural languages Character recognition Automation pattern recognition Filters Sorting computer vision Feature extraction Writing

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Off-Line Handwritten Character recognition of Devnagari Script

Off-Line Handwritten Character Recognition of Devnagari Scri...

引用

International Conference on Document Analysis and recognition

作者： U. Pal N. Sharma T. Wakabayashi F. Kimura Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Tsu Japan

In this paper we present a system towards the recognition of off-line handwritten characters of Devnagari, the most popular script in India. The features used for recognition purpose are mainly based on directional information obtained from the arc tangent of the gradient. To get the feature, at first, a 2times2 mean filtering is applied 4 times on the gray level image and a non-linear size normalization is done on the image. The normalized image is then segmented to 49times49 blocks and a Roberts filter is applied to obtain gradient image. Next, the arc tangent of the gradient (direction of gradient) is initially quantized into 32 directions and the strength of the gradient is accumulated with each of the quantized direction. Finally, the blocks and the directions are down sampled using Gaussian filter to get 392 dimensional feature vector. A modified quadratic classifier is applied on these features for recognition. We used 36172 handwritten data for testing our system and obtained 94.24% accuracy using 5-fold cross-validation scheme.

关键词： Character recognition Handwriting recognition Filters Filtering pattern recognition Image segmentation Automation computer vision System testing Natural languages

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Handwritten Bangla Compound Character recognition Using Gradient Feature

Handwritten Bangla Compound Character Recognition Using Grad...

引用

International Conference on Information Technology (ICIT)

作者： U. Pal T. Wakabayashi F. Kimura Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Tsu Mie Japan

recognition of handwritten characters of Indian script is difficult because of the presence of many complex shaped compound characters (cluster characters) as well as variability involved in the writing style of different individuals. This paper deals with recognition of off-line Bangla handwritten compound characters using modified quadratic discriminant function (MQDF). The features used for recognition purpose are mainly based on directional information obtained from the arc tangent of the gradient. To get the feature, at first, a 2 times 2 mean filtering is applied 4 times on the gray level image and a non-linear size normalization is done on the image. A Roberts filter is then applied on the normalized image to obtain gradient image. Next, the arc tangent of the gradient (direction of gradient) is initially quantized into 32 directions and the strength of the gradient is accumulated with each of the quantized direction. Finally, the frequencies of these directions are down sampled using Gaussian filter to get 392 dimensional feature vectors. Using 5-fold cross validation technique we obtained 85.90% accuracy from a dataset of Bangla compound characters containing 20,543 samples.

关键词： Character recognition Handwriting recognition Filters pattern recognition Filtering Automation Information technology computer vision Writing Frequency

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A System for Off-Line Oriya Handwritten Character recognition Using Curvature Feature

A System for Off-Line Oriya Handwritten Character Recognitio...

引用

International Conference on Information Technology (ICIT)

作者： U. Pal T. Wakabayashi F. Kimura Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Tsu Mie Japan

In this paper we present a system towards the recognition of off-line Oriya handwritten characters. Since most of the Oriya characters have curve-like stroke, we use curvature feature for the recognition purpose. To get the feature, at first, the input image is size normalized and segmented into 49times49 blocks. Curvature is then computed using bi-quadratic interpolation method and quantized into 3 levels according to concave, linear and convex regions. Next direction of gradient is quantized into 32 levels with pi/16 intervals, and strength of the gradient is accumulated in each of the 32 directions and in each of the 3 curvature levels of every block. A spatial resolution is made to get 7times7 blocks from 49times49 blocks and a directional resolution is made to get 8 directions from 32 directions. Using curvature features for 3 levels we get 1176 (7times7 blocks times 8 directions times 3 levels) dimensional features. Finally using principal component analysis we reduce the dimension 1176 to 392 and this 392 dimensional feature vector is fed to a quadratic classifier for recognition. We tested 18190 samples of Oriya handwritten samples and obtained 94.60% accuracy from our proposed system.

关键词： Character recognition Shape Handwriting recognition computer vision Spatial resolution Speech recognition Information technology pattern recognition Image segmentation Interpolation

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Local Structure Detection with Orientation-invariant Radial Configuration

Local Structure Detection with Orientation-invariant Radial ...

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Conference on computer vision and pattern recognition (CVPR)

作者： Lech Szumilas Rene Donner Georg Langs Allan Hanbury Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria

Local image descriptors have proved themselves as useful tools for many computer vision tasks such as matching points between multiple images of a scene and object recognition. Current descriptors, such as SIFT, are designed to match image features with unique local neighborhoods. However, the interest point detectors used with SIFT often fail to select perceptible local structures in the image, and the SIFT descriptor does not directly encode the local neighborhood shape. In this paper we propose a symmetry based interest point detector and radial local structure descriptor which consistently captures the majority of basic local image structures and provides a geometrical description of the structure boundaries. This approach concentrates on the extraction of shape properties in image patches, which are an intuitive way to represent local appearance for matching and classification. We explore the specificity and sensitivity of this local descriptor in the context of classification of natural patterns. The implications of the performance comparison with standard approaches like SIFT are discussed.

关键词： Detectors Shape computer vision Layout Object recognition

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A comparision of Model-based methods for knee cartilage segmentation

A comparision of Model-based methods for knee cartilage segm...

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2nd International Conference on computer vision Theory and Applications, VISAPP 2007

作者： Cheong, J. Faggian, N. Langs, G. Suter, D. Cicuttini, F. Dept. of Electrical Dept. of Computer Systems Engineering Monash University Australia Clayton School of Information Technology Monash University Australia Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria Dept. of Epidemiology Dept. of Preventive Medicine Monash University Australia

Osteoarthritis is a chronic and crippling disease affecting an increasing number of people each year. With no known cure, it is expected to reach epidemic proportions in the near future. Accurate segmentation of knee cartilage from magnetic resonance imaging (MRI) scans facilitates the measurement of cartilage volume present in a patient's knee, thus enabling medical clinicians to detect the onset of osteoarthritis and also crucially, to study its effects. This paper compares four model-based segmentation methods popular for medical data segmentation, namely Active Shape Models (ASM) (Cootes et al., 1995), Active Appearance Models (AAM) (Cootes et al., 2001), Patch-based Active Appearance Models (PAAM) (Faggian et al., 2006), and Active Feature Models (AFM) (Langs et al., 2006). A comprehensive analysis of how accurately these methods segment human tibial cartilage is presented. The results obtained were benchmarked against the current "gold standard" (cartilage segmented manually by trained clinicians) and indicate that modeling local texture features around each landmark provides the best results for segmenting human tibial cartilage.

关键词： Medical imaging

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Text/Graphics Separation in Color Maps

Text/Graphics Separation in Color Maps

引用

International Conference on Computing: Theory and Applications, ICCTA

作者： Partha Pratim Roy Josep Llados Umapada Pal Computer Science Department Universitat Autònoma de Barcelona Barcelona Bellaterra Spain Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata Kolkata India

Text/graphics separation in document image analysis is one of the main concerns in present research work. The complexity enhances when both text and graphics overlap in the context of maps in color images. This paper discusses a number of improvements to text/graphics separation methods to make it suitable for maps. Emphasize is given to the overlapping regions of text and graphics. It also discusses a method of color separation using clustering method for the purpose of text/graphics separation

关键词： computer graphics Image color analysis Image segmentation Histograms Bit error rate computer vision Text analysis Clustering methods Engineering drawings Testing

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A New Image Compression Method Based on Primal Sketch Model

A New Image Compression Method Based on Primal Sketch Model

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zheng Li Ruxin Gao Chengen Guo Junyu Dong Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China Lotus Hill Institute of Computer Vision and Information Science China Ocean University of China China

In this paper, we introduce the primal sketch model which might lead to a new image compression method. The primal sketch model integrates two modeling schemes for two type components in natural images: the sketchable and the non-sketchable parts. The sketchable part explains the structural components of the image by using a hidden layer of image primitives. The non-sketchable part denotes the remaining textural components without distinguishable elements by Markov random field models for texture images. The primitives in the image representation are not independent but organized as a sketch graph. The whole image can be coded by a sketch graph with a primitive dictionary and texture descriptors. Such a lossy coding scheme could achieve the compression ratio of 20 to 40 for natural images. With the similar visual effect, the coding length of JFEG2000 is about 1.5 to 3 times higher. This promising compression method could be applied to some situations such as wireless transmission where the bandwidth is critical and low quality images are still acceptable.

关键词： Image coding Dictionaries Pixel Markov random fields Image representation Bandwidth Image storage Psychology Mathematical model Image segmentation

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Machine Dating of Handwritten Manuscripts

Machine Dating of Handwritten Manuscripts

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International Conference on Document Analysis and recognition

作者： U. Garain S. Parui T. Paquet L. Heutte Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India Laboratoire LITIS EA 4051 UFR des Sciences Université de Rouen Saint Etienne du Rouvray France

This paper presents a pioneering study on automatic dating of handwritten manuscripts. Analysis of handwriting style forms the core of the dating method. Initially, it is hypothesized that a manuscript can be dated, to a certain level of accuracy, by looking at the way it is written. The hypothesis is then verified with real samples of known dates. A general framework is proposed for machine dating of handwritten manuscripts. Experiments on a database containing manuscripts of Gustave Flaubert (1821- 1880), the famous French novelist reports about 62% accuracy when manuscripts are dated within a range of five calendar years with respect to their exact year of writing.

关键词： Testing Humans Calendars computer vision pattern recognition Databases Writing Watermarking Error analysis Libraries

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Motion Analysis of Endovascular Stent-Grafts by MDL Based Registration

Motion Analysis of Endovascular Stent-Grafts by MDL Based Re...

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International Conference on computer vision (ICCV)

作者： Georg Langs Nikos Paragios Rene Donner Pascal Desgranges Alain Rahmouni Hicham Kobeiter GALEN Group Laboratoire de Mathématiques Appliquées aux Systàmes Ecole Centrale de Paris France Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group University of Technology Vienna Austria University of Paris XII Paris France

The endovascular repair of a traumatic rupture of the thoracic aorta - that would otherwise lead to the death of the patient - is performed by delivering a stent-graft into the vessel at the rupture location. The age range of the affected patients is large and the stent-graft will stay in the body for the remaining life. The technique is relatively new, and no experience with regard to long-term effects, and durability exists. To predict long-term complications, such as ruptures or destructive interactions with surrounding tissue during the life of the patient, it is important to understand the - rather intense and constant - movement of the stent- graft during the cardiac cycle. A computed tomography with heart gating (gated CT) acquires sequences that show the region of the stent-graft at different time points. We analyze the motion of stent-grafts with a model based approach. Stent-grafts are represented as sparse sets of axis points extracted from the gated CT, and motion patterns are captured by a minimum description length based group-wise registration of the stent-graft at different time points. No parameterization or a priori definition of the topology is necessary, and highly variable elasticity properties in the data volume can by accounted for by the sparse statistical model, that captures correlations and motion components of the stent-graft. We report results for deformation models and registration accuracy for 5 patients.

关键词： Motion analysis Computed tomography Biomedical imaging Heart Buildings computer graphics pattern recognition Image processing Hospitals Data mining

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