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6th National Conference on computer vision, Pattern Recognition, image processing and Graphics, NCVPRIPG 2017

作者： Mandal, Srimanta Rajagopalan, A.N. Image Processing and Computer Vision Lab Department of Electrical Engineering IIT Madras Chennai600036 India

ISBN: (纸本)9789811300196

Super-resolving a noisy image is a challenging problem, and needs special care as compared to the conventional super resolution approaches, when the power of noise is unknown. In this scenario, we propose an approach to super-resolve single noisy image by minimizing nuclear norm in a virtual sparse domain that tunes with the power of noise via parameter learning. The approach minimizes nuclear norm to explore the inherent low-rank structure of visual data, and is further augmented with coarse-to-fine information by adaptively re-aligning the data along the principal components of a dictionary in virtual sparse domain. The experimental results demonstrate the robustness of our approach across different powers of noise. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Optical resolving power

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Character-based car plate detection and localization

Character-based car plate detection and localization

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International Conference on Information Science, Signal processing and Their Applications

作者： Setumin, S. Sheikh, U.U. Abu-Bakar, S.A.R. Computer Vision Video and Image Processing Research Lab. Department of Microelectronics and Computer Universiti Teknologi Malaysia Malaysia

ISBN: (纸本)9781424471676

In this paper we address the issue of locating non-standard Malaysian car license plate. Instead of searching the region for the plate, we directly locate the alphanumeric characters of the car plate. In this manner, we remove issues such as plate size variations and plates on black colored vehicles. Our main goal is to locate and extract the alphanumeric characters of Malaysian special plates. These special plates do not follow the normal standard car plates' format as they may contain italic, cursive and connected letters, and of different fonts. Using several parameters such as pixel compactness, angles, and projection histogram, we use ruledbased technique to locate and detect these special characters of the car plates. The results have shown that we are able to automatically locate with an accuracy of95%. © 2010 IEEE.

关键词： License plates (automobile)

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Gender estimation based on physiological features of the face

Gender estimation based on physiological features of the fac...

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International Conference on Information Science, Signal processing and Their Applications

作者： Ting, C.H. Sheikh, U.U. Abu-Bakar, S.A.R. Computer Vision Video and Image Processing Research Lab. Department of Microelectronics and Computer Engineering Universiti Teknologi Malaysia Malaysia

ISBN: (纸本)9781424471676

In this paper, we present a gender estimation technique that will determine whether a person looking at the camera is a male or female. Several facial features extracted from a face are passed to post-image-processing operations before they are sent to a rule-base classifier. We applied our technique to both static passport-like photos as well as several video sequences consisting of a single face each. Our database also contains images of females wearing headscarf as well as bald men. Our initial results showed a very promising outcome. For static face images, we obtained an accuracy of 100% correct gender estimation for females and 98% for males while for video sequences, the accuracy obtained was 87.5% for females and 70% for males. © 2010 IEEE.

关键词： Video recording

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On averaging face images for recognition under pose variations

On averaging face images for recognition under pose variatio...

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作者： Zhang, Xiaozheng Zhao, Sanqiang Gao, Yongsheng Computer Vision and Image Processing Lab Institute for Integrated and Intelligent Systems Griffith University Australia

ISBN: (纸本)9781424421756

Recently, psychological studies showed that averaging human face images greatly improves the performance of face recognition under various pose, illumination, expression, and/or aging conditions. This paper investigates quantitatively the mechanism of the face averaging process in face recognition specifically against pose variations. Facilitated with 3D face dataset, the process of face averaging is tested on face images free from human errors and misalignments. Single images are chosen as gallery and the averaged views as probe in all the experiments. Three different scenarios are experimented, i.e., identification using single gallery images, identification using different gallery images, and averaging using unbalanced range of input image. The experimental results show that the averaging process under pose variations is equivalent to generating a face view in an average pose and the improvement in face recognition is subject to the conditions that the gallery pose is close to the average probe pose. © 2008 IEEE.

关键词： Face recognition

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Appearance based 3d object recognition using IPCA-ICA 21

Appearance based 3d object recognition using IPCA-ICA

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21st Congress of the International Society for Photogrammetry and Remote Sensing, ISPRS 2008

作者： Ananthashayana, V.K. Asha, V. Image Processing and Computer Vision Lab Department of Computer Science and Engineering M.S.Ramaiah Institute of Technology Bangalore India

Fast incremental non Gaussian directional analysis (IPCA-ICA) is proposed as a linear technique for recognition [1]. The basic idea is to compute the principal components as sequence of image vectors incrementally, without estimating the covariance matrix and at the same time transforming these principal components to the independent directions that maximize the non-Gaussianity of the source. In this paper we utilize the IPCA-ICA technique for 3D Object recognition by employing its neural network architecture. We illustrate the potential of IPCA-ICA on a database of 1440 images of 20 different objects captured by CCD camera. The excellent recognition rates achieved in all the performed experiments indicates that the present method is well suited for appearance based 3D object recognition. © 2008 International Society for Photogrammetry and Remote Sensing. All rights reserved.

关键词： Principal component analysis

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Depth estimation and inpainting with an unconstrained camera

Depth estimation and inpainting with an unconstrained camera

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2010 21st British Machine vision Conference, BMVC 2010

作者： Bhavsar, Arnav V. Rajagopalan, A.N. Image Processing and Computer Vision Lab. Department of Electrical Engineering Indian Institute of Technology Madras Chennai India

ISBN: (纸本)1901725405

Unrestricted camera motion and the ability to operate over a range of lens parameters are often desirable when using an off-the-shelf camera. Variations in intrinsic and extrinsic parameters induce defocus and pixel motion, both of which relate to scene structure. We propose a depth estimation approach by elegantly coupling the motion and defocus cues. We further advocate a natural extension of our framework for inpainting both depth and image, using the motion cue. Unlike traditional inpainting, our approach also considers defocus blur. This ensures that the image inpainting is coherent with respect to defocus. We use the belief propagation method in our estimation approach, which also handles occlusions and uses the color image segmentation cue. © 2010. The copyright of this document resides with its authors.

关键词： Cameras

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Entropy: A New Parameter for image Deciphering

Entropy: A New Parameter for Image Deciphering

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International Conference on Recent Trends in Machine Learning, IOT, Smart Cities and Applications, ICMISC 2020

作者： Cheggoju, Naveen Nawandar, Neha K. Satpute, Vishal R. Image Processing and Computer Vision Lab Department of Electronics and Communication Engineering Visvesvaraya National Institute of Technology Nagpur India

ISBN: (纸本)9789811572333

Data and information, these two terms may look quite similar and also sometimes used with the same meaning. But in-depth, these terms are completely different from each other. This paper mainly focuses on this difference to extract the encrypted information from the data (importantly image data). Here, every aspect of the study and the way of formulation are explained using "Einstein’s theory of relativity" and "Arrow of time" for better understanding. Einstein’s theory is used to explain "how similar things can be seen in different ways?" (here data and information) and arrow of time is used to explain "how the correct information can be extracted from the data?". To explain this concept, an image encrypted using a chaotic logistic map is used. The edge information present in this data is taken as the parameter to differentiate the unorganized data and organized data (correct information). Here, a new parameter called "Randomness parameter (Rp)" is introduced, which gives the entropy (randomness) of the data. The outcome of this parameter is used to differentiate the data and correct information. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Entropy

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Inferring image transformation and structure from motion-blurred images

Inferring image transformation and structure from motion-blu...

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2010 21st British Machine vision Conference, BMVC 2010

作者： Chandramouli, Paramanand Rajagopalan, A.N. Image Processing and Computer Vision Lab. Department of Electrical Engineering Indian Institute of Technology Madras Chennai India

ISBN: (纸本)1901725405

This paper deals with the problem of estimating structure of 3D scenes and image transformations from observations that are blurred due to unconstrained camera motion. Initially, we consider a fronto-parallel planar scene and relate the reference image of the scene to its motion-blurred observation by finding the reference image transformations. The blur kernel at every image point can be determined from these transformations. For 3D scenes, the extent of blurring in the image is related to the camera motion as well as the scene structure. We propose a technique to estimate the scene depth with the knowledge of the estimated image transformations. The proposed method is validated by testing on real and synthetic experiments. © 2010. The copyright of this document resides with its authors.

关键词： Cameras

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Automatic detection of renal rejection after kidney transplantation

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International Congress Series 2005年 1281卷 773-778页

作者： Yuksel, S.E. El-Baz, A. Farag, A.A. Abo El-Ghar, M.E. Eldiasty, T.A. Ghoneim, M.A. Computer Vision and Image Processing Lab University of Louisville Louisville KY 40292 United States Mansoura University Urology and Nephrology Center Mansoura Egypt

Acute rejection is the most important reason of graft failure after kidney transplantation, and early detection is crucial to survive the kidney function. Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) is an imaging modality where a contrast agent (such as Gd-DTPA) is introduced into the kidney and rapid and repeated images are taken, which allows both the anatomic and functional information of the kidney to be monitored. Using these images, this paper introduces an accurate method for the segmentation of the kidney from the surrounding structures by introducing a shape model of the kidney into the external energy component of the deformable models. Secondly, registration algorithms are employed to account for the motion of the kidney due to patient breathing and finally, the perfusion curves obtained from the cortex that show the transportation of the contrast agent into the tissue are given for future classification of normal and acute rejection transplants. Applications of the proposed algorithms yield promising results. © 2005.

关键词： Contrast agents Deformable models Dynamic MRI Gd-DTPA Kidney transplantation Mutual information Renal rejection

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Segmentation of building facade domes

Segmentation of building facade domes

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17th Iberoamerican Congress on Progress in Pattern Recognition, image Analysis, computer vision, and Applications, CIARP 2012

作者： Shalunts, Gayane Haxhimusa, Yll Sablatnig, Robert Vienna University of Technology Computer Vision Lab. Austria Vienna University of Technology Pattern Recongition and Image Processing Lab. Austria

ISBN: (纸本)9783642332746

Domes are architectural structural elements typical for ecclesiastical and secular grand buildings, like churches, mosques, palaces, capitols and city halls. The current paper targets the problem of segmentation of domes within the framework of architectural style classification of building facades. We perform segmentation of building facade domes by combining bilateral symmetry detection, graph-based segmentation approaches and image analysis and processing technics into a single method. Our algorithm achieves good segmentation results on buildings belonging to variety of architectural styles, such as Renaissanse, Neo-Renaissance, Baroque, Neo-Baroque, Neoclassical and Islamic. © 2012 Springer-Verlag.

关键词： Domes

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