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OHCS: A Database for Handwritten Atomic Odia Character Recognition 5

OHCS: A Database for Handwritten Atomic Odia Character Recog...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Mohapatra, Ramesh Kumar Mishra, Tusar Kanti Panda, Sandeep Majhi, Banshidhar Natl Inst Technol Comp Sci & Engn Rourkela 769008 India

ISBN: (纸本)9781467385640

In this paper, a complete database of handwritten atomic Odia characters is suggested. the first version of the database has been modeled and named OHCSv1.0 (Odia handwritten character set). the database comprises of 17,100 transcribed characters, each collected twice from 150 unique people at different point of time. Each character has 300 number of occurrences. the character images are standardized to a size of 6 4 x 6 4 pixels. A novel framework for perceiving transcribed Odia characters from this database has also been proposed. the character images are gathered into various groups in view of their shape components utilizing an incremental spectral clustering algorithm. During testing, affinity of probe character to a cluster is first decided. Subsequently, the trained classifier recognizes the character inside the cluster. Suitable simulation has been carried out to validate the scheme.

关键词： Character recognition

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Recognizing Newborns using Binocular Region 5

Recognizing Newborns using Binocular Region

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Parmar, Chandani Vishwamitra, L. K. Patel Coll Sci & Technol Dept Comp Sci & Engn Bhopal India

ISBN: (纸本)9781467385640

Existing approaches on newborn identification focuses on recognizing them using face, inked footprints, and palm prints. While palm and inked footprints are intrusive modalities, face modality suffers from non-cooperative nature of newborns. In this research, we investigate utilization of binocular region for recognizing newborns, as this region is considered to be relatively stable in face biometrics literature. We collect a database consisting of 402 face images pertaining to 50 babies of less than 6 months of age. A set of experiments pertaining to various descriptors, including local binary patterns, dense scale invariant feature transform, and Gabor features, along with subspace learning using principal component analysis, linear discriminant analysis, and independent component analysis. Recognition performance of various approaches are compared with respect to face and binocular modalities. Verification results are reported in terms of Receiver operating characteristics curves respectively. the results show that binocular can outperform face as a modality for newborn recognition.

关键词： Principal component analysis

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Classification of Brain MR images using Discrete Wavelet Transform and Random Forests 5

Classification of Brain MR Images using Discrete Wavelet Tra...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Nayak, Deepak Ranjan Dash, Ratnakar Majhi, Banshidhar Natl Inst Technol Dept Comp Sci & Engn Rourkela 769008 India

ISBN: (纸本)9781467385640

Development of computer-aided diagnosis (CAD) systems for early detection of the pathological brain is essential to save medical resources. In recent years, a variety of techniques have been proposed to upgrade the system's performance. In this paper, a new automatic CAD system for brain magnetic resonance (MR) image classification is proposed. the method utilizes two-dimensional discrete wavelet transform to extract features from the MR images. the dimension of the features have been reduced using principal component analysis (PCA) and linear discriminant analysis (LDA), to obtain the more significant features. Finally, the reduced set of features are applied to the random forests classifier to determine the normal or pathological brain. A standard dataset, Dataset-255 of 255 images (35 normal and 220 pathological) is used for the validation of the proposed scheme. To improve the generalization capability of the scheme, 5-fold stratified cross-validation procedure is utilized. the results of the experiments reveal that the proposed scheme is superior to other state-of-the-art techniques in terms of classification accuracy with substantially reduced number of features.

关键词： Discrete wavelet transforms

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Automated Detection and Classification of Mass from Breast Ultrasound images 5

Automated Detection and Classification of Mass from Breast U...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Menon, Radhika V. Raha, Poulami Kothari, Shweta Chakraborty, Sumit Chakrabarti, Indrajit Karim, Rezaul IIT Kharagpur Dept E & ECE Kharagpur W Bengal India IPGMER SSKM Kolkata India CMSDH Kolkata India

ISBN: (纸本)9781467385640

this paper introduces a computer aided diagnosis (CAD) technique for segmentation of mass in breast ultrasound (BUS) images followed by an efficient classification of the image into benign or malignant one. the presence of speckle noise, low contrast and blurred boundary of mass in a BUS image makes it challenging to determine the mass, which is the region of interest (ROI) in the current work. Detecting an accurate ROI in turn results in efficient feature extraction and classification. In current work, image enhancement and speckle noise reduction are implemented for preprocessing in a simple but efficient way through filtering techniques. the results of the preprocessing stage are as effective as those obtained using traditional speckle reduction anisotropic diffusion (SRAD) algorithm. ROI is then accurately determined on preprocessed image by employing local region based active contour method. BUS images are classified through textural, morphological and histogram oriented feature metrics in this work. the obtained features are dimensionally reduced using principal component analysis (PCA) and classified through support vector machine (SVM) method. the proposed method is tested on several images and found to be very effective having an accuracy of 95.7% with very high specificity and positive predictive value (PPV).

关键词： breast ultrasound CAD active contours geometric features PCA classification SVM

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Segmenting Printed Text and Handwritten Annotation by Spectral Partitioning 5

Segmenting Printed Text and Handwritten Annotation by Spectr...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Pandey, Shilpa Harit, Gaurav Indian Inst Technol Comp Sci & Engn Jodhpur 342011 Rajasthan India

ISBN: (纸本)9781467385640

this paper addresses the problem of segmenting handwritten annotations on scientific research papers. the motivation of this work is to geometrically segment the complex cases of handwritten annotations, including marks, cuts and special symbols along, with the regular text. Our work particularly focuses on documents that have multi-oriented handwritten [1] annotations rather than annotations in controlled scenario [2]. Spectral Partitioning is adopted as the segmentation scheme to separate the printed text and annotations. A new feature Envelope Straightness is developed and included in our feature set. this leads to an improvement of accuracy over the state-of-the-art features. the experiments are performed on two datasets: 40 documents authored by two writers from IAM dataset, comprising only printed and handwritten text and a self created dataset of 40 scientific papers from various proceedings annotated by a reader, comprising varied types of annotations. In the framework of spectral partitioning, our feature set has achieved a recall of 98.39% for printed text and precision of 85.40% for handwritten annotations on our dataset. For IAM dataset our feature set has achieved a recall of 81.89% for printed text and a precision of 69.67% for handwritten annotations. the results achieved on both dataset are better compared with results obtained using [3] [1].

关键词： computer vision

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Iris Liveness Detection Using Texture Segmentation 5

Iris Liveness Detection Using Texture Segmentation

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Kumar, Mohit Puhan, N. B. Indian Inst Technol Bhubaneswar Sch Elect Sci Bhubaneswar Orissa India

ISBN: (纸本)9781467385640

In order to chisel an iris recognition system and pass in the iris liveness test, an attacker can create semitransparent contact lens spoofing. Such a contact lens is transparent around the iris center and has fake iris texture of another person printed around the outer region. In this paper, such fake iris images are synthetically created which can obviate sleuthing even after using pupillary light reflex technique. thereafter, new liveness detection is proposed to determine the perceptually invisible boundary between the fake and original iris textures. Response of Gaussian derivative filters with multiple scales and orientations at each pixel location is clustered using K- means to ascertain regions with different textures. To give robustness to the algorithm, it is iterated a certain number of times and a threshold mechanism is imposed to find the correct boundary. the proposed method is shown to achieve high liveness performance by generating a set of 600 fake iris images from the UPOL iris database.

关键词： Iris recognition liveness detection fake semitransparent contact lens texture segmentation

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Rank Level Fusion in Multibiometric Systems 5

Rank Level Fusion in Multibiometric Systems

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Sharma, Renu Das, Sukhendu Joshi, Padmaja Ctr Dev Adv Comp Bombay Maharashtra India Indian Inst Technol Madras Tamil Nadu India

ISBN: (纸本)9781467385640

Multibiometric systems have recently become a preferred option for human identification over the unibiometric systems. It increases the recognition rate and confidence in the final decision, and simultaneously reduces the failure to enroll rate (FER). For identification mode, rank level fusion is a feasible option as incompatibility and normalization issues present at the score level fusion are not prominent at this level and also sufficient information is present to fuse as opposed to the decision level fusion. We propose an improvement in existing rank level fusion techniques using two levels of hierarchy. Series and parallel combinations are proposed to combine the output of various rank level fusion techniques. Two formulations of series and parallel combinations are extensively evaluated on multi-algorithm, multi-instance and multi-modal biometric systems created from three publicly available datasets: (i) NIST BSSR1 [1] multimodal biometric score database, (ii) Face Recognition Grand Challenge V2.0 [2] and (iii) LG4000 [3] iris images.

关键词： Face recognition

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Place of Articulation from Direct Imaging for Validation of Its Estimation from Speech Analysis for Use in Speech Training 5

Place of Articulation from Direct Imaging for Validation of ...

引用

5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Nataraj, K. S. Pandey, Prem C. Indian Inst Technol Dept Elect Engn Bombay 400076 Maharashtra India

ISBN: (纸本)9781467385640

Place of articulation obtained by analysis of the speech signal is useful for visual feedback of articulatory efforts for speech training of hearing impaired children and for improving pronunciation by learners of second languages. Its estimation by direct imaging of the oral cavity is needed for validating the estimation from the speech signal. For such applications, an automated technique is presented for estimating the place of articulation by graphical processing of the upper and lower contours of the oral cavity image. It iteratively estimates the axial curve as an axis of symmetry of the oral cavity, such that the curve approximately bisects the normals to it. Distance between the contours along the normal to the axial curve gives the oral cavity opening and position of the smallest opening provides the place of articulation. the values estimated using the automated technique closely matched those obtained by manual marking of the visually estimated place of maximum constriction for the oral cavity images of vowels, stops, and fricatives, from the XRMB and MRI databases.

关键词： axial curve oral cavity opening place of articulation speech training

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Large-scale Virtual Texturing on a Distributed Rendering System 5

Large-scale Virtual Texturing on a Distributed Rendering Sys...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Revanth, N. R. Narayanan, P. J. Int Inst Informat Technol Ctr Visual Informat Technol Hyderabad 500032 Andhra Pradesh India

ISBN: (纸本)9781467385640

there has been a profound interest of late in the digitization and reconstruction of historical monuments. Rendering massive monument models requires a cluster of workstations because of the computational infeasibility of rendering over a single machine. Moreover, interactive rendering of these massive models in an immersive environment is only possible over a cluster of machines. In this paper, we present a design of distributed rendering system to efficiently handle models with massive textures. A server holds the skeleton of the whole model and divides the screen space balancing the rendering load among multiple clients. Each client loads only the required geometry and textures to render its sub-scene. We present a virtual texturing method for handling massive textures over the distributed rendering system. these textures are combined into a texture atlas which is split into equally sized tiles. A virtual texture is built over this atlas with each pixel representing a tile in the atlas. An efficient caching module loads only the required tiles into the memory, that are identified using the virtual texture. A fragment shader uses the virtual texture as a mapping to the physical texture in memory to generate the fragments. We demonstrate the performance of our system over a 350M triangles and 500 gigapixel textured model of Vittala temple.

关键词： Rendering (computer graphics)

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2-D Dual Tree Complex Wavelet Transform (DT-CWT) Based Fingerprint Ridge Structure Quality Enhancement 5

2-D Dual Tree Complex Wavelet Transform (DT-CWT) Based Finge...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Kundargi, Jayshree M. Karandikar, R. G. KJ Somaiya Coll Engn Dept Elect Engn Bombay 77 Maharashtra India KJ Somaiya Coll Engn Dept Elect & Tele Engn Bombay 77 Maharashtra India KJ Somaiya Coll Engn Bombay 77 Maharashtra India

ISBN: (纸本)9781467385640

Nowadays fingerprint is widely used to ascertain identity of an individual. the performance of an automated fingerprint verification system depends on the quality of the fingerprint image captured by the sensor. In this paper we propose fingerprint ridge structure quality enhancement using 2D Dual Tree Complex Wavelet Transform (DT-CWT). the DT-CWT provides multiscale description of fingerprint images with good directional selectivity. the DT-CWT transforms fingerprint images into six directionally selective subbands at multiple scales. the wavelet coefficients in all subbands are compensated adaptively based on the compensation coefficients obtained from the singular values of subbands of fingerprint image and a referred Gaussian template. the original image is then reconstructed using inverse DT-CWT. the experimental results show that the DT-CWT is more effective than the Discrete Wavelet Transform in terms of improvement in singular point detection accuracy.

关键词： Fingerprint verification system quality of fingerprint image 2-D Dual Tree Complex Wavelet Transform Discrete Wavelet Transform Gaussian template singular point detection

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