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检索条件"任意字段=Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing"

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Automatic Perspective Camera Calibration Based on an Incomplete Set of Chessboard Markers

Automatic Perspective Camera Calibration Based on an Incompl...

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Alessandro Bevilacqua Alessandro Gherardi Ludovico Carozza ARCES University of Bologna Bologna Italy

The measurement in metric units from a perspective view of a real world object is an important task in many computer vision applications. The goal of the perspective calibration is to map the reference coordinates of the 3D object into the 2D image coordinates. This is usually done by recovering the perspective transformation parameters by presenting to the camera a view of a known calibration pattern. Many of the available algorithms require to process all the points of the calibration pattern in order to recover the transformation parameters effectively. The approach we present for the computation of the inverse perspective transformation does not require to consider all the grid points. Rather, a grid matching between the 3D points projection and the model is performed exploiting a graph based approach. Extensive experiments have proved the efficacy of the algorithm in different application fields such as camera calibration and automotive headlight beam characterization.

关键词： Cameras Calibration Layout Pattern matching Robot kinematics Navigation computer vision Automotive engineering Robotics and automation Optical computing

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Animation Geometry Compression Using the Linear Discriminant Analysis

Animation Geometry Compression Using the Linear Discriminant...

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： A.R. Vamsidhar P.K. Bora Sanjib Das Department of Electronics and Communication Engineering Indian Institute of Technology Guwahati Guwahati India

We propose a new method to compress the geometry component of 3D animation sequence. It is based on the linear discriminant analysis (LDA) of the animation geometry data. The redundancy across the animation frames has been exploited by using the LDA in the temporal direction. Owing to the redundancy between the frames of a class, the covariance matrix of that class for the LDA computation may become singular. To overcome this drawback, we first transform the data into a new basis using the principal component analysis (PCA) and then apply the LDA on a few principal components. The reconstruction is simple and involves two stages: firstly for the LDA and then for the PCA. The experimental results show that the proposed method has the advantage of better reconstruction error at high compression ratios.

关键词： Animation Geometry Linear discriminant analysis Principal component analysis image coding image reconstruction Surface texture Rough surfaces Surface roughness Redundancy

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Colour Retinal image Enhancement Based on Domain Knowledge

Colour Retinal Image Enhancement Based on Domain Knowledge

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Gopal Datt Joshi Jayanthi Sivaswamy Centre for Visual Information Technology International Institute of Information Technology Hyderabad India

Retinal images are widely used to manually or automatically detect and diagnose many diseases. Due to the complex imaging setup, there is a large luminosity and contrast variability within and across images. Here, we use the knowledge of the imaging geometry and propose an enhancement method for colour retinal images, with a focus on contrast improvement with no introduction of artifacts. The method uses non-uniform sampling to estimate the degradation and derive a correction factor from a single plane. We also propose a scheme for applying the derived correction factor to enhance all the colour planes of a given image. The proposed enhancement method has been tested on a publicly available dataset. Results show marked improvement over existing methods.

关键词： Retina image enhancement Lighting image segmentation Color Diseases Cameras Surface topography Automatic control Histograms

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Audio-Visual Person Authentication with Multiple Visualized-Speech Features and Multiple Face Profiles

Audio-Visual Person Authentication with Multiple Visualized-...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Amitava Das Ohil K. Manyam Makarand Tapaswi Microsoft Research India India

We present an Audio-visual person authentication system which extracts several novel ldquovisualized-speech-featuresrdquo (VSF) from the spoken-password and multiple face profiles using a simple user-interface and combine these features to deliver high performance and resilience against imposter attacks. The spoken password is converted to a string of images formed by several visualized speech features. A compressed form of these VSFs preserves speaker identity in a compact manner. Simulation results on an in-house 210-user AV-user-ID database collected with wide variations of users in real-life office environments demonstrate separable distributions of client and imposter scores (0% EER), while offering low storage and computational complexities compared to conventional AV user-recognition methods.

关键词： Authentication Visualization Resilience image converters Speech image coding Computational modeling image databases Spatial databases Visual databases

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MRC Compression of Compound Documents Using Threshold Segmentation, Iterative Data-Filling and H.264/AVC-INTRA

MRC Compression of Compound Documents Using Threshold Segmen...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Alexandre Zaghetto Ricardo L. de Queiroz Debargha Mukherjee ENE Universidade de Brasília Brasília DF Brasil Universidade de Brasilia Brasilia DF BR Hewlett-Packard Laboratory Palo Alto CA USA Hewlett Packard Labs Palo Alto CA USA

The Mixed Raster Content (MRC) ITU document compression standard (T.44) specifies a multi-layer representation of a compound document. It is expected that higher compression can be achieved if more efficient compression standards are used to compress each layer. In this paper we present an MRC compound document codec that uses H.264/AVC operating in INTRA mode to encode Background/Foreground layers and JBIG2 to encode the binary Mask layer. We also present a threshold-based layer segmentation algorithm and an iterative data-filling algorithm for redundant regions. The result is an unrivaled performance for compressing compound documents as demonstrated by our experiments.

关键词： image coding Automatic voltage control PSNR Transform coding image segmentation Codecs Iterative algorithms Video compression computer vision computer graphics

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Fast and Secure Real-Time Video Encryption

Fast and Secure Real-Time Video Encryption

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： C. Narsimha Raju Ganugula Umadevi Kannan Srinathan C.V. Jawahar International Institute of Information Technology Hyderabad India

Advances in digital content transmission have increased in the past few years. Security and privacy issues of the transmitted data have become an important concern in multimedia technology. In this paper, we propose a computationally efficient and secure video encryption algorithm. This makes secure video encryption feasible for real-time applications without any extra dedicated hardware. We achieve computational efficiency by exploiting the frequently occurring patterns in the DCT coefficients of the video data. Computational complexity of the encryption is made proportional to the influence of the DCT coefficients on the visual content. On an average, our algorithm takes only 8.32 ms of encryption time per frame.

关键词： Cryptography Data security Discrete cosine transforms Streaming media Videoconference Computational efficiency Costs Information security Codecs computer vision

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Palm Leaf Manuscript/Color Document image Enhancement by Using Improved Adaptive Binarization Method

Palm Leaf Manuscript/Color Document image Enhancement by Usi...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Sridhar Cherala Priti P. Rege College of Engineering Pune India

This paper presents a new color document image binarization that is suitable for palm leaf manuscripts and color document images. The proposed method consists of two steps: a pre-processing procedure using low-pass Wiener filter, and contrast adaptive binarization for segmentation of text from the background. Firstly, in the pre-processing stage, low-pass Wiener filter is used to eliminate noisy areas, smoothing of background texture as well as contrast enhancement between background and text areas. Finally, binarization is performed by using contrast adaptive binarization method in order to extract useful text information from low quality document *** techniques are tested on a set of palm leaf manuscript images/color document images. The performance of the algorithm is demonstrated on by palm leaf manuscripts/color documents distorted with show-through effects, uneven background color and localized spot.

关键词： image enhancement Gray-scale Pixel Color Laplace equations Optical character recognition software Character recognition Text analysis Wiener filter image segmentation

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Discriminant Function Revisited for Incremental Learning

Discriminant Function Revisited for Incremental Learning

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： R.K. Agrawal Rajni Bala Manju Bala School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi India

Discriminant function is commonly and effective methodology for solving classification problems. However, it is computationally efficient when all features are considered simultaneously. But sometimes all the features do not contribute significantly to classification. Also the noisy attributes sometimes may decrease the accuracy of classifier. So before classification feature selection is used as a pre-processing step. When the features are added one by one in forward feature selection method using batch mode, to compute discriminant function involves huge computation. In this paper, an incremental discriminant function for multivariate normal distribution datasets is proposed. The proposed incremental discriminant function is computationally efficient over batch discriminant function in terms of time. The effectiveness of the proposed incremental discriminant function has been demonstrated through experiments on different datasets. It is found on the basis of experiments that the incremental discriminant function has an equivalent power compared to batch discriminant function in terms of classification accuracy. However, the proposed incremental discriminant function has very high speed efficiency in comparison to batch discriminant function.

关键词： Costs Filters Pattern classification Error analysis computer vision computer graphics image processing Electronic mail Gaussian distribution Training data

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Face Expression Recognition through Broken Symmetries

Face Expression Recognition through Broken Symmetries

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Vito Di Gesù Bertrand Zavidovique Marco Elio Tabacchi CITC - Università degli Studi di Palermo Italy IEF - University of Paris Sud XI France DMA - Università degli Studi di Palermo E Istituto Nazionale di Ricerche Demopolis Italy

Security systems, criminology, physical access control and man-machine interactions are examples of applications where recognition of human faces may be crucial. In the present paper a new signature, based on a measure of axial symmetry called DST, is proposed as a significant feature to analyze facial expressions. The measure of symmetry is an elaborate difference between the internal and external symmetry kernels of an object. The idea here is to use the evolution of the symmetry measure of a face over an ordered set of its sub-images. We claim that different evolutionary trends will represent different face expressions. The proposed signature has been tested on several face databases (psychological image collection at stirling and jaffe). Experimental results indicate that the proposed signature characterizes normal from happy expression with a good accuracy.

关键词： Face recognition Face detection Humans Kernel Psychology computer vision image recognition Man machine systems Application software Muscles

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Object Mining Using a Matching Graph on Very Large image Collections

Object Mining Using a Matching Graph on Very Large Image Col...

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： James Philbin Andrew Zisserman Visual Geometry Group Department of Engineering Science University of Oxford UK

Automatic organization of large, unordered image collections is an extremely challenging problem with many potential applications. Often, what is required is that images taken in the same place, of the same thing, or of the same person be conceptually grouped together. This work focuses on grouping images containing the same object, despite significant changes in scale, viewpoint and partial occlusions, in very large (1M+) image collections automatically gathered from Flicker. The scale of the data and the extreme variation in imaging conditions makes the problem very challenging. We describe a scalable method that first computes a matching graph over all the images. image groups can then be mined from this graph using standard clustering techniques. The novelty we bring is that both the matching graph and the clustering methods are able to use the spatial consistency between the images arising from the common object (if there is one). We demonstrate our methods on a publicly available dataset of 5 K images of Oxford, a 37 K image dataset containing images of the Statue of Liberty, and a much larger 1M image dataset of Rome. This is, to our knowledge, the largest dataset to which image-based data mining has been applied.

关键词： Clustering algorithms Clustering methods Data mining Information retrieval image retrieval computer vision computer graphics image processing Computational geometry Application software

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