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What can an image of a smooth Lambertian surface tell about camera nonlinearity?

What can an image of a smooth Lambertian surface tell about ...

引用

2012 9th Conference on computer and Robot vision, CRV 2012

作者： El-Melegy, Moumen T. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Electrical Engineering Department Assiut University Assiut 71516 Egypt

ISBN: (纸本)9780769546834

This paper investigates the use of a single image of a smooth Lambertian surface to calibrate and remove some image nonlinearities due to the imaging device. To the best of our knowledge, this has not been addressed before in the literature. We show that this is possible, both theoretically and practically, taking advantage of some local shading measures that vary nonlinearly as a function of luminance and geometric nonlinearities (e.g., gamma correction and lens distortion). This can work as a basis for developing a simple method to estimate these nonlinearities from a single image. Several experiments are reported to validate the proposed method. © 2012 IEEE.

关键词： Cameras

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Heat kernels for non-rigid shape retrieval: Sparse representation and efficient classification

Heat kernels for non-rigid shape retrieval: Sparse represent...

引用

2012 9th Conference on computer and Robot vision, CRV 2012

作者： Abdelrahman, Mostafa El-Melegy, Moumen Farag, Aly Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States Electrical Engineering Department Assiut University Assiut 71516 Egypt

ISBN: (纸本)9780769546834

One of the major goals of computer vision and machine intelligence is the development of flexible and efficient methods for shape representation. This paper presents an approach for shape retrieval based on sparse representation of scale-invariant heat kernel. We use the Lap lace-Beltrami eigen functions to detect a small number of critical points on the shape surface. Then a shape descriptor is formed based on the heat kernels at the detected critical points for different scales, combined with the normalized eigen values of the Lap lace-Beltrami operator. Sparse representation is used to reduce the dimensionality of the calculated descriptor. The proposed descriptor is used for classification via the collaborative representation-based classification with regularized least square algorithm. We compare our approach to two well-known approaches on two different data sets: the nonrigid world data set and the SHREC 2011. The results have indeed confirmed the improved performance of the proposed approach, yet reducing the time and space complicity of the shape retrieval problem. © 2012 IEEE.

关键词： computer vision

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FREQUENCY-DOMAIN analysis OF DISCRETE WAVELET TRANSFORM COEFFICIENTS AND THEIR ADAPTIVE SHRINKAGE FOR ANTI-ALIASING

FREQUENCY-DOMAIN ANALYSIS OF DISCRETE WAVELET TRANSFORM COEF...

引用

IEEE International Conference on image Processing

作者： Eunjung Chae Eunsung Lee Wonseok Kang Younghoon Lim Junghoon Jung Taechan Kim Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea System LSI Samsung Electronics Co. Ltd Suwon Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479923427

We present an antialiasing method using combined wavelet-Fourier transform and spatially adaptive shrinkage of the transform coefficients. Traditional antialiasing methods employ a simple low-pass filter onto the entire image, so the resulting image loses not only aliasing artifacts but also high-frequency components such as edges and ridges. The proposed algorithm analyzes the property of the LL subband of the discrete wavelet transform (DWT), and reduces aliasing artifacts using patch-adaptive shrinkage of the DWT coefficients. More specifically, an antialiased LL subband is obtained using adaptive patch-based aliasing reduction. To detect an aliased region, we subtract the discrete Fourier transform (DFT) coefficients of the LL subband from the DFT coefficients of antialiased LL subband. The detected aliasing artifacts in the LH, HL, and HH subbands are reduced by patch-wise adaptive shrinkage of the transform coefficients. The resulting antialiased image is obtained using the inverse DWT. The aliasing artifacts can be efficiently reduced by adaptively shrinking wavelet transform coefficients for preserving high-frequency image details. The proposed antialiasing algorithm is suitable for removing aliasing artifacts which frequently occur in imaging sensors with limited resolution.

关键词： Anti-aliasing wavelet-Fourier transform image enhancement patch-adaptive shrinkage antialiasing image enhancement Aliasing shrinkage Artifacts subband domain analysis Coefficients Sensors (image) Frequency-domain analysis discrete Fourier transform

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Performance-analysis-based acceleration of image quality assessment

Performance-analysis-based acceleration of image quality ass...

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2012 IEEE Southwest Symposium on image analysis and Interpretation, SSIAI 2012

作者： Phan, Thien Sohoni, Sohum Chandler, Damon M. Larson, Eric C. Laboratory of Computational Perception and Image Quality School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078 United States Laboratory of Computer Architecture Education Simulation and Research School of Electrical and Computer Engineering Oklahoma State University Stillwater OK 74078 United States DUB Group Department of Electrical Engineering University of Washington Seattle WA 98195 United States

ISBN: (纸本)9781467318303

Two stages are commonly employed in modern algorithms of image/video quality assessment (QA): (1) a local frequency-based decomposition, and (2) block-based statistical comparisons between the frequency coefficients of the reference and distorted images. This paper presents a performance analysis of and techniques for accelerating these stages. We specifically analyze and accelerate one representative QA algorithm recently developed by the authors (Larson and Chandler, 2010). We identify the bottlenecks from the abovementioned stages, and we present methods of acceleration using integral images, inline expansion, a GPGPU implementation, and other code modifications. We show how a combination of these approaches can yield a speedup of 47x. © 2012 IEEE.

关键词： image quality

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Modified full abundance-constrained spectral unmixing

Modified full abundance-constrained spectral unmixing

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High-Performance Computing in Remote Sensing II

作者： Wong, Englin Chang, Chein-I Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780819492791

Abundance fully constrained least squares (FLCS) method has been widely used for spectral unmixing. A modified FCLS (MFCLS) was previously proposed for the same purpose to derive two iterative equations for solving fully abundance-constrained spectral unmixing problems. Unfortunately, its advantages have not been recognized. This paper conducts a comparative study and analysis between FCLS and MFCLS via custom-designed synthetic images and real images to demonstrate that while both methods perform comparably in unmixing data, MFCLS edges out FCLS in less computing time. © 2012 SPIE.

关键词： Iterative methods

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Produce recognition system using data mining algorithm

Produce recognition system using data mining algorithm

引用

IEEE International Conference on Control System, Computing and engineering (ICCSCE)

作者： J. K. Chaw M. M. Mokji Computer Vision Video and Image Processing (CvviP) Laboratory Department of Microelectronic and Computer Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia

Produce recognition system is a system that can categorize types of vegetables and fruits based on features extracted from the images. However, there are numerous features that can be extracted from fruits and vegetables such as colour, texture and shape. As a result, it is effort consuming to identify suitable features ad hoc. Thus, data mining is required to discover the most discriminative features for recognition. This paper aims to extend the usage of data mining algorithm to image domain. Data mining algorithm is preferred to other feature selection algorithms because it discovers nuggets of knowledge that can be understood by human whereas classic feature selection techniques provide outputs that can only be managed by learning algorithms.

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A design method for Malaysian car plates character segmentation based on skew correction

A design method for Malaysian car plates character segmentat...

引用

IEEE International Conference on Control System, Computing and engineering (ICCSCE)

作者： Jinn-Li Tan S. A. R Abu-Bakar Computer Vision Video and Image Processing Department of Microelectronics and Computer Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Malaysia

This paper presents a license plate character segmentation method in the context of Malaysian cars. First of all, pre-processing steps will enhance the image before Laplacian pyramid takes place. For a proper binarization, Laplacian pyramid which up-sampled the image from an image lower in the pyramid when the image is captured under low resolution. By using Sobel edge detector and then median filtering, circumscribe rectangle of minimum area is formed and the angle is calculated. At the same time, the area of characters is focussed. The characters are then selected based on connected component analysis after applying Niblack's threshold. Our goal is to segment the characters properly from the steps mentioned. Therefore, our algorithm tries to find the best point to segment the characters using little prior knowledge. Experimental shows promising results on the flexibility of the proposed design method.

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Rolling shutter bundle adjustment

Rolling shutter bundle adjustment

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： Johan Hedborg Per-Erik Forssén Michael Felsberg Erik Ringaby Computer Vision Laboratory Department of Electrical Engineering Linköping University Sweden

This paper introduces a bundle adjustment (BA) method that obtains accurate structure and motion from rolling shutter (RS) video sequences: RSBA. When a classical BA algorithm processes a rolling shutter video, the resultant camera trajectory is brittle, and complete failures are not uncommon. We exploit the temporal continuity of the camera motion to define residuals of image point trajectories with respect to the camera trajectory. We compare the camera trajectories from RSBA to those from classical BA, and from classical BA on rectified videos. The comparisons are done on real video sequences from an iPhone 4, with ground truth obtained from a global shutter camera, rigidly mounted to the iPhone 4. Compared to classical BA, the rolling shutter model requires just six extra parameters. It also degrades the sparsity of the system Jacobian slightly, but as we demonstrate, the increase in computation time is moderate. Decisive advantages are that RSBA succeeds in cases where competing methods diverge, and consistently produces more accurate results.

关键词： Cameras Jacobian matrices Barium Trajectory Indexes Solid modeling Geometry

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What Can an image of a Smooth Lambertian Surface Tell About Camera Nonlinearity?

What Can an Image of a Smooth Lambertian Surface Tell About ...

引用

Canadian Conference on computer and Robot vision, CRV

作者： Moumen T. El-Melegy Aly A. Farag Electrical Engineering Department Assiut University Asyut Egypt Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

关键词： Cameras Distortion measurement Lenses Calibration Shape Lighting Surface treatment

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DIRECT METHOD FOR SHAPE RECOVERY FROM POLARIZATION AND SHADING

DIRECT METHOD FOR SHAPE RECOVERY FROM POLARIZATION AND SHADI...

引用

IEEE International Conference on image Processing

作者： Ali H. Mahmoud Moumen T. El-Melegy Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Electrical Engineering Department Assiut University Assiut Egypt

Polarization imaging can give information about surface shape, and roughness. Polarization has been used for shape recovery, but with convex/concave reconstruction ambiguity. In this paper, we present a direct method to shape recovery using both polarization and shading that resolves this ambiguity, without the need for nonlinear optimization routines. Several experiments on synthetic and real datasets are reported to evaluate the proposed method. The method consistently outperforms some well-known methods based on polarization information alone.

关键词： Shape Surface reconstruction Azimuth image reconstruction Surface treatment Cameras

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