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International conference on systems, Signals and image processing, IWSSIP

作者： Krzysztof Malczewski Faculty of Electronics and Telecommunications Poznan University of Technology Poznan Poland

ISBN: (纸本)9781509063451

Super-resolution reconstruction algorithms have been extensively studied for the last years. However, despite the progress made in this field, many issues remain to be solved. Some of them are basically omitted and their importance is trivialized. Routinely, for instance, researchers are willing to make the relative motion model simpler than it should be considered. The commonly applied non-rigid registration method being manually defined does not capture the real motion characteristics that could occur in image sequences. This work extends Iterative Back Projection (IBP) framework in several ways. It nests image priors, deblurring and a discrete dense displacement sampling for the deformable registration of high-resolution images at its core. Applying these constraints to a global optimum of the cost function can be calculated efficiently exploiting dynamic programming. It leads to the smoothness of the deformations of the image's features. This paper proposes an improved super-resolution method while making no compromise on image quality. The author experiment results confirmed the empirical observations, in particular, that the state of the art registration algorithm and blur and noise estimate procedures, as well as image priors, lead to promising results.

关键词： Kernel Spatial resolution Algorithm design and analysis Signal resolution Estimation

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A novel method for the extraction of primary visual features from an image through intelligent feature descriptors

A novel method for the extraction of primary visual features...

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International conference on Recent Innovations in Signal processing and Embedded systems (RISE)

作者： Abhinav V. Deshpande M. Monica Subashini School of Electronics Engineering V.I.T University Vellore India School of Electrical Engineering V. I. T. University Vellore India

ISBN: (纸本)9781509047611;9781509047604

As far as the safety of a driver is concerned, more focus should be put on correct interpretation and information which is conveyed by a traffic sign, while driving a vehicle along the road. A sign board can be thought of as an emblem which disseminates important and meaningful information regarding the potential hazards prevailing among road users comprising roadways cladded with snowfall, construction worksites or repairing of roads taking place and telling the people to follow an alternative route. It alerts the person who is passing through the road about the maximum possible extremity that his vehicle is trying to achieve indicating slowing down the speed of vehicle since chances of having collision cannot be ruled out. With constant increasing of the training database size, not only there cognition accuracy, but also the computation complexity should be considered in designing a feasible recognition approach. The traffic sign images were acquired from the image database and were subjected to some pre-processing techniques such as conversion of the original RGB images into HSV Color Space, Adjustment of the Contrast of the Color images as well as applying the Histogram of Oriented Gradients (HOG) algorithm in which the process of extraction and plotting of the HOG features from a given image is performed that is most popular amongst the feature extraction algorithms. In the future, we will concentrate on detecting, recognizing as well as classifying a particular sign board.

关键词： Feature extraction Vehicles image color analysis image recognition image databases Classification algorithms Shape

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Brain tumor detection and classification in MRI images using image and data mining

Brain tumor detection and classification in MRI images using...

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International conference on Recent Innovations in Signal processing and Embedded systems (RISE)

作者： Saumya Chauhan Aayushi More Ritumbhra Uikey Pooja Malviya Asmita Moghe Department of Information Technology UIT RGPV BHOPAL India Department of IT UIT RGPV BHOPAL India

ISBN: (纸本)9781509047611;9781509047604

Brain tumor is a perilous disease which causes brain damage. So, detection and classification of brain tumor in early stage is necessary. In the proposed work MRI brain images are pre-processed by median filtering. To segregate lesion from image, color based segmentation and edge detection is performed. Multiple feature extraction schemes, namely histogram of oriented gradients and gray level co-occurrence matrix are used to represent the images. All the extracted features are stored in a transactional database to which IBkLG classifier (Instance based K-Nearest using Log and Gaussian weight Kernels) has been applied using WEKA 3.9 tool, to classify the tumor into normal benign or malignant. The classification accuracy is observed found to be 86.6%.

关键词： Feature extraction Tumors image segmentation image color analysis image edge detection Data mining Clustering algorithms

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A hybrid DCT-DHE approach for enhancement of low contrast underwater images

A hybrid DCT-DHE approach for enhancement of low contrast un...

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International conference on Recent Innovations in Signal processing and Embedded systems (RISE)

作者： Nisheeth Dubey Sandeep Kumar Tiwari Pankaj Sharma Dept CSE/IT VITM Gwalior

ISBN: (纸本)9781509047611;9781509047604

In this research, presented an underwater image enhancement (IE) making use of discrete cosine transform (DCT) with dynamic histogram equalization (DHE) algorithm. The main issue in IE underwater images are blur impact, low-contrast, nonuniform illumination, because of turbulence in flow of water. In underwater images, it impacts the scattering of light from a few particles of various sizes, low force caused by low visibility conditions, suspended development particles. In this approach, firstly take RGB to YCBCR format for further processing. The new result is applied on peak signal Noise Ratio (PSNR) and Entropy. This calculation is contrasted and three calculations, to be specific DCP[1], brightness bi histogram equalization(BBHE), Contrast Enhance method. The proposed algorithm decribes that better performance as compared to other algorithms.

关键词： Histograms Discrete cosine transforms image color analysis image enhancement Entropy Color

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Robust pose recognition using deep learning

Robust pose recognition using deep learning

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International conference on Computer Vision and image processing, CVIP 2016

作者： Mohanty, Aparna Ahmed, Alfaz Goswami, Trishita Das, Arpita Vaishnavi, Pratik Sahay, Rajiv Ranjan Department of Electrical Engineering Indian Institute of Technology Kharagpur Kharagpur India Department of Computer Science and Technology Indian Institute of Engineering Science and Technology Shibpur Kolkata India Sardar Vallabhai National Institute of Technology Surat Surat India

ISBN: (纸本)9789811021060

Current pose estimation methods make unrealistic assumptions regarding the body postures. Here, we seek to propose a general scheme which does not make assumptions regarding the relative position of body parts. Practitioners of Indian classical dances such as Bharatnatyam often enact several dramatic postures called Karanas. However, several challenges such as long flowing dresses of dancers, occlusions, change of camera viewpoint, poor lighting etc. affect the performance of state of- the-art pose estimation algorithms [1, 2] adversely. Body postures enacted by practitioners performing Yoga also violate the assumptions used in current techniques for estimating pose. In this work, we adopt an image recognition approach to tackle this problem. We propose a dataset consisting of 864 images of 12 Karanas captured under controlled laboratory conditions and 1260 real-world images of 14 Karanas obtained from Youtube videos for Bharatnatyam. We also created a new dataset consisting of 400 real-world images of 8 Yoga postures. We use two deep learning methodologies, namely, convolutional neural network (CNN) and stacked auto encoder (SAE) and demonstrate that both these techniques achieve high recognition rates on the proposed datasets. © Springer Science+Business Media Singapore 2017.

关键词： image recognition

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A double-integrator system for distributed optimization of convex cost functions 29

A double-integrator system for distributed optimization of c...

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第29届中国控制与决策会议

作者： Ngoc-Tu Tran Xuan Feng Wen-Yuan Xu Na Zhan Xi Wang School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control(Huazhong University of Science and Technology) Ministry of Education Hubei Electric Power Company

ISBN: (纸本)9781509046584

In this paper,the distributed optimization problem is investigated under a second-order multi-agent *** the proposed algorithm,each agent solves the optimization via local computation and information exchange with its neighbors through the communication ***,in comparison with the existing second-order distributed optimization algorithms,the proposed algorithm is much simpler due to one coupled information exchange among the agents is *** achieve the optimization,the distributed algorithm is proposed based on the consensus method and the gradient *** optimal solution of the problem is thus obtained with the design of Lyapunov function and the help of LaSallel's Invariance Principle.A numerical simulation example and comparison of proposed algorithm with existing works are presented to illustrate the effectiveness of the theoretical result.

关键词： Second-order multi-agent systems Distributed optimization Consensus Lyapunov function Gradient algorithm

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Heuristic-modified region filling algorithms for A-B connection searching problem

Heuristic-modified region filling algorithms for A-B connect...

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International conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service (TELSIKS)

作者： Vladan Vučković Boban Arizanović Faculty of Electronic Engineering University of Nis Nis Serbia

ISBN: (纸本)9781538618011

This paper presents optimized connection searching method based on region filling algorithms. The proposed method is optimized using the heuristic and is intended for maze-solving. In specific cases, the proposed algorithm performs better than variants which do not use heuristic and it depends on the maze structure and position of the starting and ending pixel.

关键词： Floods Heuristic algorithms Algorithm design and analysis Standards Time complexity Filling image processing

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Comparative study of AES, RSA, genetic, affine transform with XOR operation, and watermarking for image encryption

Comparative study of AES, RSA, genetic, affine transform wit...

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International conference on Recent Innovations in Signal processing and Embedded systems (RISE)

作者： Avinash Ray Anjali Potnis Prashant Dwivedy Shahbaz Soofi Uday Bhade Department of Electrical & Electronics Engineering National Institute of Technical Teachers' Training & Research Bhopal Madhya Pradesh INDIA

ISBN: (纸本)9781509047611;9781509047604

In present scenario whole world is moving towards digital communication for fast and better communication. But in this a problem arises with security i.e. when we have to transmit information (either data or image) over internet or to store information at any random location then its security is very important. To protect our information from hackers we use a technique i.e. Encryption. In this paper we use image as information and use different types of encryption techniques to encrypt it and protect it from hackers. After that we find various parameters from each image encryption technique and then compare each technique's parameters from one another. After that we search for the best result and then proceed forward with that technique for future scope.

关键词： Encryption Watermarking Genetic algorithms Ciphers Public key PSNR

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Video Quality Assessment Metrics for Infrared Video Frames using Different Edge Detection algorithms

Video Quality Assessment Metrics for Infrared Video Frames u...

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International conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC)

作者： K. Sai Prasad Reddy K. Nagabhushan Raju Department of Electronics Sri Krishnadevaraya University Anantapuramu India Department of Instrumentation Sri Krishnadevaraya University Anantapuramu India

ISBN: (纸本)9781538632444

Infrared signal processing algorithms and architectures are important for the development of a high performance infrared imaging systems. Infrared signal processing deals with two types of processing sensor signal processing and infrared image processing for contrast enhancement and target detection. The sensor signal processing primarily deals with non uniformity correction for infrared sensors. Assessing the quality of the Infrared video frame is a complex and firm process since human's opinion is affected by physical and psychological parameters. Infrared Video frame quality assessment plays an important role in the field of video processing. Structural Similarity Index has become a standard among image quality metrics. It is a framework for quality assessment based on the degradation of structural information of video frame. In this paper SSIM values are computed and compared for Infrared video frames by applying different edge detection approaches by using different color models to assess the quality of the frames. Experimental results comparisons demonstrate the effectiveness of the proposed method.

关键词： image edge detection image color analysis Laplace equations Detectors Indexes Computational modeling Mathematical model

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The study of effectiveness of a high-performance crystal lattice parametric identification algorithm based on CUDA technology

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Journal of Physics: conference Series 2019年第5期1368卷

作者： Shirokanev, A S Kirsh, D V Kupriyanov, A V Samara National Research University Moskovskoe Shosse 34A Samara Russia 443086 Image Processing Systems Institute of RAS - Branch of the FSRC “Crystallography and Photonics” RAS Molodogvardejskaya street 151 Samara Russia 443001

The study of substances with a crystal structure is a complex multi-step process. The key step in the crystalline substance analysis is the unit cell parameter estimation. The estimation of the crystal lattice unit cell parameters is a particular problem that involves the search of the crystal lattice model’s parameters according to the information which can be extracted from the substance. In these recent times, the most accurate information about the substance structure can be obtained with the electron microscope whose linear resolution is high enough to observe the atomic structure of a substance. The problem of parameter estimation in this case means the reconstruction of the three-dimensional crystal lattice with 2-dimentional images received by an electron microscope, and the estimation of the crystal lattice unit cell parameters by reconstructed lattice. In the previous papers the crystal lattice parametric identification algorithms based on solving the local optimization problem were presented. However, the analysis of a large crystal lattice database requires a lot of computations. In this paper, a high-performance crystal lattices parametric identification algorithm using the CUDA technology is proposed. The investigation of the algorithm effectiveness is carried out on the GPU GeForce NVidia GTX 1070 Ti. With data dimension more than 32 translations the acceleration is higher than 70. The algorithm runs more efficiently at the use of a large number of CUDA-blocks.

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