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Iris recognition using partial sum of second order Taylor Series Expansion 16

Iris recognition using partial sum of second order Taylor Se...

引用

10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Shekar, B. H. Bhat, Sharada S. Mangalore Univ Dept Comp Sci Mangalore Karnataka India Govt Arts & Sci Coll Karwar Karnataka India

ISBN: (纸本)9781450347532

Iris is presently one among the most sought after traits in biometric research. Extracting well-suited features from iris has been a favourite topic of the researchers. This paper proposes a novel iris feature extraction technique based on partial sum of second order Taylor series expansion (TSE). The finite sum of TSE computed on an arbitrary small neighbourhood on multiple scales can approximate the function extremely well and hence provides a powerful mechanism to extract the complex natured localised features of iris structure. To compute the higher order derivatives of TSE, we propose kernel structures by extending the Sobel operators. Extensive experiments are conducted with multiple scales on IITD, MMU v-2 and CASIA v-4 distance databases and comparative analysis is performed with the existing algorithms to substantiate the performance of the proposed method.

关键词： Taylor Series Expansion Iris Feature Extraction Iris Recognition Biometrics

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A Distribution-Independent Risk Estimator for image Denoising 16

A Distribution-Independent Risk Estimator for Image Denoisin...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Subramanian, Babu Kishore Gupta, Ashutosh Seelamantula, Chandra Sekhar Sattva MedTech Bangalore 560025 Karnataka India Indian Space Res Org Ahmadabad 380015 Gujarat India Indian Inst Sci Bangalore 560012 Karnataka India

ISBN: (纸本)9781450347532

We address the problem of image denoising for an additive white noise model without placing any restrictions on the statistical distribution of noise. We assume knowledge of only the first-and second-order noise statistics. In the recent mean-square error (MSE) minimization approaches for image denoising, one considers a particular noise distribution and derives an expression for the unbiased risk estimate of the MSE. For additive white Gaussian noise, an unbiased estimate of the MSE is Stein's unbiased risk estimate (SURE), which relies on Stein's lemma. We derive an unbiased risk estimate without using Stein's lemma or its counterparts for additive white noise model irrespective of the noise distribution. We refer to the MSE estimate as the generic risk estimate (GenRE). We demonstrate the effectiveness of GenRE using shrinkage in the undecimated Haar wavelet transform domain as the denoising function. The estimated peak-signal-to-noise-ratio (PSNR) using GenRE is typically within 1% of the PSNR obtained when optimizing with the oracle MSE. The performance of the proposed method is on par with SURE for Gaussian noise distribution, and better than SURE-based methods for other noise distributions such as uniform and Laplacian distribution in terms of both PSNR and structural similarity (SSIM).

关键词： Risk estimation undecimated wavelet transform image denoising wavelet shrinkage generic risk estimation (GenRE)

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User guided generation of corroded objects 16

User guided generation of corroded objects

引用

10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Jain, Nisha Ranjan, Rohit Kalra, Prem Kumar, Subodh Indian Inst Technol Delhi New Delhi India

ISBN: (纸本)9781450347532

Rendering of corrosion often requires pain-staking modeling and texturing. On the other hand, there exist techniques for stochastic modeling of corrosion, which can automatically perform simulation and rendering under control of some user-specified parameters. Unfortunately, these parameters are non-intuitive and have a global impact. It is hard to determine the values of these parameters to obtain a desired look. For example, in real life corrosion gets influenced by both internal object-specific geometric factors, like sharp corners and curvatures, and external interventions like scratches, blemishes etc. Further, a graphics designer may want to selectively corrode areas to obtain a particular scene. We present a technique for user guided spread of corrosion. Our framework encapsulates both structural and aesthetic factors. Given the material properties and the surrounding environmental conditions of an object, we employ a physio-chemically based stochastic model to deduce the decay of different points on that object. Our system equips the user with a platform where the imperfections can be provided by either manual or systematic interference on a rendering of the three dimensional object. We demonstrate several user guided characteristic simulations encompassing varied influences including material, object characteristics and environment conditions. Our results are visually validated to understand the impact of imperfections with elapsed time.

关键词： Corrosion Simulation Rendering User guided Curvatures

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Mosaicing Deep Underwater imagery 16

Mosaicing Deep Underwater Imagery

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Purohit, Kuldeep Vasu, Subeesh Rajagopalan, A. N. Jyothi, V. Bala Naga Raju, Ramesh IIT Madras Madras Tamil Nadu India Natl Inst Ocean Technol Madras Tamil Nadu India

ISBN: (纸本)9781450347532

Numerous sources of distortions render mosaicing of underwater (UW) images an immensely challenging effort. Methods that can process conventional photographs (terrestrial/aerial) fail to deliver the desired results on UW images. Taking the sources of underwater degradations into account is central to ensuring quality performance. The work described in this paper specifically deals with the problem of mosaicing deep UW images captured by Remotely Operated Vehicles (ROVs). These images are mainly degraded by haze, color changes, and non-uniform illumination. We propose a framework that restores these images in accordance with a suitably derived degradation model. Furthermore, our scheme harnesses the scene geometry information present in each image to aid in constructing a mosaic that is free from artifacts such as local blurring, ghosting, double contouring and visible seams. Several experiments on real underwater images sequences have been carried out to demonstrate the performance of our mosaicing pipeline along with comparisons.

关键词： Mosaic dehazing illumination correction scattering underwater

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Pap Smear image Classification Using Convolutional Neural Network 16

Pap Smear Image Classification Using Convolutional Neural Ne...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Bora, Kangkana Chowdhury, Manish Mahanta, Lipi B. Kundu, Malay K. Das, Anup K. Inst Adv Study Sci & Technol Cent Computat & Numer Studies Gauhati Assam India KTH Sch Technol & Hlth Stockholm Sweden Indian Stat Inst Machine Intelligence Unit Kolkata India Ayursundra Healthcare Pvt Ltd Dept Pathol Gauhati Assam India

ISBN: (纸本)9781450347532

This article presents the result of a comprehensive study on deep learning based computer Aided Diagnostic techniques for classification of cervical dysplasia using Pap smear images. All the experiments are performed on a real indigenous image database containing 1611 images, generated at two diagnostic centres. Focus is given on constructing an effective feature vector which can perform multiple level of representation of the features hidden in a Pap smear image. For this purpose Deep Convolutional Neural Network is used, followed by feature selection using an unsupervised technique with Maximal Information Compression Index as similarity measure. Finally performance of two classifiers namely Least Square Support Vector Machine (LSSVM) and Softmax Regression are monitored and classifier selection is performed based on five measures along with five fold cross validation technique. Output classes reflects the established Bethesda system of classification for identifying pre-cancerous and cancerous lesion of cervix. The proposed system is also compared with two existing conventional systems and also tested on a publicly available database. Experimental results and comparison shows that proposed system performs efficiently in Pap smear classification.

关键词： Pap smear image Deep learning LSSVM Softmax Regression

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Complementary Tracker's Fusion for Robust Visual Tracking 16

Complementary Tracker's Fusion for Robust Visual Tracking

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Kakanuru, Sumithra Rapuru, Madan Kumar Mishra, Deepak Gorthi, Sai Subrahmanyam Indian Inst Space Sci & Technol Dept Avion Thiruvananthapuram Kerala India

ISBN: (纸本)9781450347532

Though visual object tracking algorithms are capable of handling various challenging scenarios individually, still none of them is robust enough to handle all the challenges simultaneously. This paper aims at proposing a novel robust tracking algorithm by elegantly fusing the frame level detection strategy of Tracking Learning & Detection (TLD) with systematic model update strategy of Kernelized Correlation Filter tracker (KCF). The motivation behind the selection of trackers is their complementary nature in handling tracking challenges. The proposed algorithm efficiently combines the two tracking algorithms based on conservative correspondence measure with strategic model updates, which takes advantages of both and outperforms them on their short-ends by the virtue of other. The proposed fusion approach is quite general and any complimentary tracker (not just KCF) can be fused with TLD to leverage the best performance. Extensive evaluation of the proposed method based on different metrics is carried out on the datasets ALOV300++, Online Tracking Benchmark (OTB) and Visual Object Tracking (VOT2015) and demonstrated its superiority in terms of robustness and success rate by comparing with state-of-theart trackers.

关键词： Visual tracking trackers fusion correspondence measure

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3D Binary Signatures 16

3D Binary Signatures

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Srivastava, Siddharth Lall, Brejesh Indian Inst Technol Dept Elect Engn Delhi India

ISBN: (纸本)9781450347532

In this paper, we propose a novel binary descriptor for 3D point clouds. The proposed descriptor termed as 3D Binary Signature (3DBS) is motivated from the matching efficiency of the binary descriptors for 2D images. 3DBS describes keypoints from point clouds with a binary vector resulting in extremely fast matching. The method uses keypoints from standard keypoint detectors. The descriptor is built by constructing a Local Reference Frame and aligning a local surface patch accordingly. The local surface patch constitutes of identifying nearest neighbours based upon an angular constraint among them. The points are ordered with respect to the distance from the keypoints. The normals of the ordered pairs of these keypoints are projected on the axes and the relative magnitude is used to assign a binary digit. The vector thus constituted is used as a signature for representing the keypoints. The matching is done by using hamming distance. We show that 3DBS outperforms state of the art descriptors on various evaluation metrics.

关键词： 3D Descriptors 3D Matching 3D Object Recognition

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Immersive Augmented Reality System for Assisting Needle Positioning During Ultrasound Guided Intervention 16

Immersive Augmented Reality System for Assisting Needle Posi...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Kanithi, Praveen Kumar Chatterjee, Jyotirmoy Sheet, Debdoot Indian Inst Technol Sch Med Sci & Technol Kharagpur W Bengal India Indian Inst Technol Elect Engn Dept Kharagpur W Bengal India

ISBN: (纸本)9781450347532

Ultrasound (US) guided intervention is a surgical procedure where the clinician makes use of imaging in realtime, to track the position of the needle, and correct its trajectory for accurately steering it to the lesion of interest. However, the needle is visible in the US image, only when aligned in-plane with the scanning plane of the US probe. In practice, clinicians often use a mechanical needle guide, thus restricting their available degrees of freedom in the US probe movement. Alternatively, during free-hand procedure, they use multiple needle punctures to achieve this in-plane positioning. Our present work details an augmented reality (AR) system for patient comfort centric aid to needle intervention through an overlaid visualization of the needle trajectory on the US frame prior to its insertion. This is implemented by continuous visual tracking of the US probe and the needle in 3D world coordinate system using fiducial markers. The tracked marker positions are used to draw the needle trajectory and tip visualized in realtime to augment on the US feed. Subsequently, the continuously tracked US probe and needle, and the navigation assistance information, would be overlaid with the visual feed from a head mounted display (HMD) for generating totally immersive AR experience for the clinician.

关键词： Augmented reality fiducial markers head mounted display image guided interventions ultrasonography

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Deep Automatic Licence Plate Recognition system 10

Deep Automatic Licence Plate Recognition system

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Jain, Vishal Sasindran, Zitha Rajagopal, Anoop Biswas, Soma Bharadwaj, Harish S. Ramakrishnan, K. R. Indian Inst Sci Bengaluru Karnataka India Myntra Designs Bengaluru Karnataka India

ISBN: (纸本)9781450347532

Automatic License Plate Recognition (ALPR.) has important applications in traffic surveillance. It is a challenging problem especially in countries like in India where the license plates have varying sizes, number of lines, fonts etc. The difficulty is all the more accentuated in traffic videos as the cameras are placed high and most plates appear skewed. This work aims to address ALPR. using Deep CNN methods for real-time traffic videos. We first extract license plate candidates from each frame using edge information and geometrical properties, ensuring high recall. These proposals are fed to a CNN classifier for License Plate detection obtaining high precision. We then use a CNN classifier trained for individual characters along with a spatial transformer network (STN) for character recognition. Our system is evaluated on several traffic videos with vehicles having different license plate formats in terms of tilt, distances, colors, illumination, character size, thickness etc. Results demonstrate robustness to such variations and impressive performance in both the localization and recognition. We also make available the dataset for further research on this topic.

关键词： Convolution Neural Network Spatial Transformer Network image Transformation Pursuit Automatic License Plate Recognition

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Automatic Detection of Malaria Infected RBCs from a Focus Stack of Bright Field Microscope Slide images 16

Automatic Detection of Malaria Infected RBCs from a Focus St...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Gopakumar, G. Swetha, M. Siva, Gorthi. Sai Subrahmanyam, G. R. K. S. Indian Inst Space Sci & Technol Dept ESS Trivandrum 695547 Kerala India Indian Inst Sci Dept Instrumentat & Appl Phys Bangalore 560012 Karnataka India Indian Inst Space Sci & Technol Dept Avion Trivandrum 695547 Kerala India

ISBN: (纸本)9781450347532

Malaria is a deadly infectious disease affecting red blood cells in humans due to the protozoan of type Plasmodium. In 2015, there is an estimated death toll of 438, 000 patients out of the total 214 million malaria cases reported worldwide. Thus, building an accurate automatic system for detecting the malarial cases is beneficial and has huge medical value. This paper addresses the detection of Plasmodium Falciparum infected RBCs from Leishman's stained microscope slide images. Unlike the traditional way of examining a single focused image to detect the parasite, we make use of a focus stack of images collected using a bright field microscope. Rather than the conventional way of extracting the specific features we opt for using Convolutional Neural Network that can directly operate on images bypassing the need for hand-engineered features. We work with image patches at the suspected parasite location there by avoiding the need for cell segmentation. We experiment, report and compare the detection rate received when only a single focused image is used and when operated on the focus stack of images. Altogether the proposed novel approach results in highly accurate malaria detection.

关键词： Malaria Diagnosis Plasmodium Falciparum CNN

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