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Anatomical model-guided segmentation of brain MR image sequences 14

Anatomical model-guided segmentation of brain MR image seque...

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9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Mondal, Prasenjit Mukhopadhyay, Jayanta Sural, Shamik Bhattacharyya, Pinak Pani Department of Computer Science and Engineering Indian Institute of Technology Kharagpur West Benagl India School of Information Technology Indian Institute of Technology Kharagpur West Benagl India Department of Radiology Quadra Medical Services Pvt. Ltd. Kolkata India

ISBN: (纸本)1595930361

this paper presents a method for segmentation of human brain magnetic resonance (MR) image sequences based on a 3D human brain model (triangulated mesh). the brain model is composed of four components, namely, cerebrum, cerebellum, brain stem and pituitary gland. Synthesized image sequences are extracted from the model at regular intervals for sagittal and coronal views as done in MR imaging. To align a series of real MR images with these synthesized cross-sections, an efficient dynamic programming based computational technique has been used that obtains the optimal synthesized cross-section sequence corresponding to the series of MR images. For automatic segmentation of anatomical structures from the MR images, each aligned synthesized cross-section is overlaid on the corresponding physical MR image by carrying out appropriate geometric transformation. this transformation produces model guided boundaries for four segments corresponding to cerebrum, cerebellum, brain stem and pituitary gland. Subsequently, these initial contours are further refined by the method of active contouring, which provides segmentation of 3D MR images into the above mentioned four parts. the proposed method compares well with the recently proposed Charged Fluid Model (CFM) based approach and level set segmentation method in terms of accuracy at a significantly lower computational cost. Copyright 2014 ACM.

关键词： image segmentation

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High throughput MR image reconstruction using compressed sensing 14

High throughput MR image reconstruction using compressed sen...

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Deka, Bhabesh Datta, Sumit Dept. of Electronics and Communication Engg. Tezpur University Tezpur Assam784028 India

ISBN: (纸本)1595930361

Magnetic resonance imaging (MRI) is an essential soft tissue imaging technique. Major limitation of this imaging technique is due to its slow acquisition. MR image reconstruction using the compressed sensing (CS) has mainly two research areas, one, how efficiently MRI data can be acquired and the other is how fast the reconstruction can be done without degrading the quality of the reconstructed images. From the recent study, it is observed that the TV-1 -2 model for MR image reconstruction from random under-sampled data gives the best result. In this paper, we propose a novel high throughput MR image reconstruction algorithm without compromising the quality. the experimental results show that the proposed method is quite efficient compared to the state-of-the-art MR image reconstruction techniques based on compressed sensing in terms of the cpu time and the quality of the reconstructed images. Copyright 2014 ACM.

关键词： Magnetic resonance imaging

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Digitization of historic inscription images using cumulants based simultaneous blind source extraction 14

Digitization of historic inscription images using cumulants ...

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Jayanthi, N. Tomar, Ayush Raj, Aman Indu, S. Chaudhury, Santanu Delhi Technological University New Delhi India Indian Institute of Technology New Delhi India

ISBN: (纸本)1595930361

In this paper a novel method to address the problem of enhancement and binarization of historic inscription images is presented. Inscription images in general have no distinction between the text layer and background layer due to absence of color difference and possess highly correlated signals and noise. the proposed technique provides a suitable method to separate the text layer from the historic inscription images by considering the problem as blind source separation which aims to calculate the independent components from a linear mixture of source signals, by maximizing a contrast function based on higher order cumulants. Further, the results are compared with existing ICA based techniques like NGFICA and Fast-ICA. Copyright 2014 ACM.

关键词： Blind source separation

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ProLoSAC : An improved RANSAC algorithm for pairwise registration of 3D point clouds 14

ProLoSAC : An improved RANSAC algorithm for pairwise registr...

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Pankaj, Dhanya S. Nidamanuri, Rama Rao Pinnamaneni, Bhanu Prasad Indian Institute of Space Science and Technology Thiruvananthapuram India Rajalakshmi Engineering College Chennai India

ISBN: (纸本)1595930361

Registration of partially overlapping 3D point clouds of an object is the initial phase in the 3D modeling pipeline. the automatic coarse alignment of a pair of 3D images is usually performed by 3D feature matching. Robust estimators like RANSAC are employed for 3D transformation estimation from point correspondences obtained by feature matching, in the presence of outliers. the number of RANSAC iterations required depends directly on the number of correspondences and inliers. Many variants of RANSAC have been proposed for the computer vision tasks like stereo matching, structure and motion estimation, image retrieval etc. this paper presents a study on the potential of two widely stated RANSAC variants - PROSAC and LoSAC - for 3D registration. Further, a new algorithm -ProLoSAC - which combines the relative merits of the two is proposed. the proposed algorithm has been evaluated on different pairs of partially overlapping 3D views of three different 3D models. the results indicate that the proposed algorithm finds the best transformation in less iteration compared to the other algorithms. Copyright 2014 ACM.

关键词： Motion estimation

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Distributed video coding using local rank transform 14

Distributed video coding using local rank transform

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Mallick, Kallol Mukherjee, Jayanta Indian Institute of Technolgy Kharagpur Kharagpur India

ISBN: (纸本)1595930361

In today's world, with advanced technology and easily available portable gadgets as enabler, video has become an important medium of communication. While, the standard H.264/AVC has produced extremely good results, it has not been suitable for this application domain as it is computationally intensive and unsuitable for low-power resources. In distributed video coding (DVC), an encoder requires less computation than the decoder, which usually runs at sites of higher computational resources. Our approach is to find out a novel approach in DVC, to reduce encoder complexity, using local rank transform (LRT). LRT relies on the relative ordering of local intensity values for application on visual correspondence problem. Use of LRT in DVC, to the best of our knowledge, has not been reported in literature before. First, we have developed techniques for image reconstruction using LRT and then design a DVC codec using it. We show analytically and by experimental results, that, in power-rate-distortion model, LRT encoder outperforms standard encoder (LDPCA in Stanford architecture) specially in low bit rate condition. Copyright 2014 ACM.

关键词： image reconstruction

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An interactive framework for reconstructing 3D neuronal structures 14

An interactive framework for reconstructing 3D neuronal stru...

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Kumar, Kanuj Natarajan, Vijay Sikdar, S.K. Srinivas, Kalyan V. Computer Science and Automation Indian Institute of Science Bangalore India Supercomputer Education and Research Centre Indian Institute of Science Bangalore India Molecular Biophysics Unit Indian Institute of Science Bangalore India

ISBN: (纸本)1595930361

Neuron reconstruction is a complex and tedious task and neurobiologists today have to rely on time-consuming manual methods. Methods that entail manual tracing may introduce systematic inaccuracies. this necessitates the use of automated methods for reconstruction of neuronal structures. Despite recent advancements, the automation of reconstruction process either does not exhibit robustness against noise of microscopy images or fails to capture precise dendritic structures. this motivates the development of semiautomated methods that require crucial but minimal expert user input. In this paper, we present a fast and interactive framework for reconstruction of neuronal structures that employs automatic methods while allowing a user to provide expert input if the results are unsatisfactory. the framework is designed as a multi-stage pipeline, where in the user provides numerical input parameters to guide the reconstruction process and validates the output of automated methods visually. the user is also assisted by the framework in calculating the optimal values of required parameters for reconstruction. the framework is also able to handle discontinuities and produce a connected geometric model of the neuron structure. Copyright 2014 ACM.

关键词： Automation

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Removing structural noise in handwriting images using deep learning 14

Removing structural noise in handwriting images using deep l...

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Chen, Gang Srihari, Sargur N. Dept. of Computer Science and Engineering University at Buffalo State of University of New York BuffaloNY14260 United States

ISBN: (纸本)1595930361

Since handwriting recognition is very sensitive to structural noise, like superimposed objects such as straight lines and other marks, it is necessary to remove noise in a preprocessing stage before recognition. Although numerous denoising approaches have been proposed, it remains a challenge. the difficulties are due to non-locality of structural noise and hard discernment between spurious and the meaningful regions. We propose a supervised approach using deep learning to remove structural noise. Specifically, we generalize the deep autoencoder into the deep denoising autoencoder (DDAE), which consists in training a neural network with noisy and clean pairs to minimize cross-entropy error. Inspired by recurrent neural networks, we introduce feedback loop from the output to enhance the "repaired" image well in the reconstruction stage in our framework. We test the DDAE model on three handwritten image data sets, and show advantages over Wiener filter, robust Boltzmann machines and deep autoencoder. Copyright 2014 ACM.

关键词： Recurrent neural networks

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Secret image sharing using fractal codes 14

Secret image sharing using fractal codes

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Acharya, Aniruddha Babu, R. Venkatesh Video Analytics Laboratory Supercomputer Education Research Center Indian Institute of Science Bangalore India

ISBN: (纸本)1595930361

Secret sharing is a well known problem of cryptography. A secret has to be shared among a group of N people, in such a way that only when at least K of them use their shares, the secret is revealed. A special case of this problem is secret image sharing, where the secret is an image. Prior work on image sharing has predominantly been visual secret sharing on binary images, where decoding is done by stacking the shares and viewing them. Some of the works address gray scale and color image sharing too. We target secret image sharing for gray scale images and propose a novel solution based on fractal encoding and decoding. the main advantage of our method as compared to the other schemes is that the space complexity of the shares is O(1). that is the sum total of space required for all the shares is independent of N. We have not seen this property in any of the previous works of image sharing. We achieve this by avoiding the use of images as shares, and using partial and modified fractal codes instead. Moreover, our method implicitly does compression along with image sharing. the proposed algorithm has decoding time complexity O(N), which is the state of the art. Experiments have shown that the proposed method is robust to security attacks. Copyright 2014 ACM.

关键词： Binary images

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Recognizing facial expressions in the orthogonal complement of principal subspace 14

Recognizing facial expressions in the orthogonal complement ...

引用

9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Agarwal, Swapna Mazumder, Sanjoy Mukherjee, Dipti Prasad Indian Statistical Institute Kolkata700108 India

ISBN: (纸本)1595930361

We present a novel framework for recognition of facial expressions from a given face image. the framework is based on the assumption that expression information lies in the subspace orthogonal to the subspace representing expressionneutral faces. For deriving the principal subspace of the face images showing no expression, PCA is used as a tool. then we derive a method to find the orthogonal complement (OC) of the subspace defined by the principal components. It is shown using different tools such as dendrogram and Davies-Bouldin cluster index that the OC of the principal subspace better represents the expressions as compared to the principal subspace in PCA analysis. We have done extensive experiments to validate the recognition capability of the proposed OC space. Two well known publicly available facial expression databases are used for the experiments. We also compare the expression discrimination capability of the OC subspace with some well known features for expression representation. the proposed framework exhibits higher (9:66% on average) recognition capability as compared to the present state-of-the-art works. Copyright 2014 ACM.

关键词： Face recognition

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Temporal stationarity based prediction method for lossless video coding 14

Temporal stationarity based prediction method for lossless v...

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9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Vaishnav, Mohit Chobey, Dinesh Kumar Tiwari, Anil Kumar LNM Institute of Information Technology India Indian Institute of Technology Jodhpur India

ISBN: (纸本)1595930361

this paper aims to propose a noble method to estimate the auto-regressive(AR) coefficients used by least-square(LS) based predictors. Estimation of this LS based predictors is computationally most complex process. this process requires a covariance matrix comprised of chosen causal pixels and also the inverse elements of the same matrix. Computational requirements of this process depends on the number of pixels for which the predictor is trained and also on the order of the predictor. Due to this high complexity, the predictor is not used practically although it provides a high compression ratio. thus, an alternative algorithm, popularly known as LOPT-3D, was proposed in literature. However, the number of pixels required for the estimation of AR parameters are still large, and thereby, making it impracticable for real-time implementations. the proposed method overcomes this limitation by effectively making use of previously estimated AR parameters. Copyright 2014 ACM.

关键词： Covariance matrix

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