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image REGULARIZATION WITH MULTIPLE morphological GRADIENT PRIORS

IMAGE REGULARIZATION WITH MULTIPLE MORPHOLOGICAL GRADIENT PR...

引用

IEEE International conference on image processing

作者： Makoto NAKASHIZUKA Faculty of Engineering Chiba Institute of Technology

ISBN: (纸本)9781467399623

In this paper, we propose an image prior based on morphological gradients for image recovery. The morphological gradient is defined as the difference between dilation and erosion of an image and approximates the image gradient. This prior provides regularization with an L_1-L_∞ norm. The regularization problem with the proposed prior is reduced to a constrained minimization problem and is solved by an augmented Lagrangian method with proximal operators. We apply the proposed prior to image denoising and demonstrate an image decomposition along with the size of the structuring element of the morphological gradients. Comparing with the total variation (Tv) norm, which is an L_1-L_2 norm, the proposed prior is superior in recovery of fine details by choice of the structuring element.

关键词： Mathematical morphology Regularization Denoising image recovery mathematical morphology Noise reduction structuring element images image decomposition Lagrangian method imagery (Psychotherapy) Gradient image image denoising

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TENSOR morphological PROFILE FOR HYPERSPECTRAL image CLASSIFICATION

TENSOR MORPHOLOGICAL PROFILE FOR HYPERSPECTRAL IMAGE CLASSIF...

引用

IEEE International conference on image processing

作者： Jie Liang Jun Zhou Yongsheng Gao Research School of Engineering Australian National University School of Information and Communication Technology Griffith University

ISBN: (纸本)9781467399623

This paper proposes a novel multi-dimensional morphology descriptor, tensor morphology profile (TMP), for hyperspectral image classification. TMP is a general framework to extract the multi-dimensional structures in high-dimensional data. The nth-order morphology profile is proposed to work with the nth-order tensor, which can capture the inner high order structures. This is different with the traditional mathematical morphology operations which are usually limited to two-dimensional data. By treating hyperspectral images a tensor, it is possible to extend the morphology to high dimensional data so that the powerful morphological tools can be used to analyze the hyperspectral images with spectral-spatial information fused. Experimental results on two commonly used hyperspectral images show that the tensor morphological profile consistently performs better than the extended morphological profile for hyperspectral image classification.

关键词： Mathematical morphology Tensor modeling Hyperspectral imaging classification

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Pedestrian Flow Counter using image processing

Pedestrian Flow Counter using Image Processing

引用

International conference on Energy, Communication, Data Analytics and Soft Computing

作者： Kartik Madhira Aditya Shukla Nirma University

ISBN: (纸本)9781538618882

This paper describes a People Counting System based on image processing techniques to count human traffic at various places like retail shops, malls, ATMs etc. The module was made using an WiFi stream from an overhead IP (Internet Protocol) CCTv camera and processed through OpenCv library in Python. The live video feed is taken frame by frame to process and morphological operations were applied to each frame to get rid of noises and get proper blobs. Next, using contours method we extract the co-ordinates of each blob and track them so that the blob can be counted in a region of frame. The accuracy of the counting depends on a number of factor such as height of camera, field of vision, camera angle, lighting etc. of which we try to discuss in this paper.

关键词： People Counter Background Subtraction Contours Blob Tracking

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A study on Down syndrome detection based on Artificial Neural Network in Ultra sonogram images

A study on Down syndrome detection based on Artificial Neura...

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2016 International conference on Data Mining and Advanced Computing, SAPIENCE 2016

作者： vincy Devi, v.K. Rajesh, R. Bharathiar University Coimbatore India Dept of Computer Applications Sree Narayana Gurukulam College of Engineering Kadayiruppu P.O. Kolenchery Ernakulam dist.Kerala India

ISBN: (纸本)9781467385947

Down syndrome is a genetic disorder in which disrupts infants, physical and cognitive development. Down syndrome is characterized by the absence of nasal bone during the late first trimester of pregnancy. Presently Down syndrome is identified by visually examining the ultra sonogram image of foetus of 11 to 13 weeks of gestation for the presence of nasal bone. The visually identification by the change in the contrast of nasal bone region of ultra sonogram is a very difficult task. So the image processing based features extraction by considering various parameters have been extremely important. This paper provides comprehensive survey on various medical imaging techniques that can be effectively used for detecting the syndrome in the early stage of pregnancy. Our proposed survey consider different methods based on the various parameters extracted using a series of operations such as Region Of Interest (ROI), Nasal Bone (NB) segmentation using morphological, Otsu thresholding and logical operations from the ultra sonogram images, both in spatial domain as well as transform domain using Discrete Cosine Transform (DCT) and wavelet transforms. The extracted data is normalized and used to train classifiers like Back Propagation Neural Network (BPNN). This paper illustrates overview of various states of methods available in the Down syndrome detection and comparison analysis of each method is discussed. © 2016 IEEE.

关键词： Feature extraction

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Comparison of standard edge detection techniques along with morphological processing and pseudo coloring in sonar image

Comparison of standard edge detection techniques along with ...

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International conference on Emerging Trends in Engineering, Technology and Science (ICETETS)

作者： U. Anitha S. Malarkkan J. Premalatha v. Manonmani Faculty of Electronics Sathyabama University Chennai Manakula Vinayagar Institute of Technology Puducherry

ISBN: (纸本)9781467367264

Object recognition and texture identification are the two main application of sonar image processing. It consists of 3 main steps such as image segmentation, object recognition and pattern identification. Before all these steps, some of the preprocessing procedure are included such as filtering of noise, edge detection etc. Many edge detection operators are available and also a mathematical modeling called morphological processing is also very useful for edge detection. Color images generally have more visual perception over gray scale and monochrome images. Therefore in this paper the standard edge detection techniques along with the morphological processing are carried out. Comparison of the result along with the pseudo colored image proves that the morphological processing along with edge detection techniques gives more information than another one. Subjective analysis tells that, this approach mainly useful for the sonar image objects consist of larger shadow regions.

关键词： image edge detection Object recognition Speckle image segmentation Sonar navigation Synthetic aperture sonar

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Numerical Mathematics and Advanced Applications 2011: Proceedings of Enumath 2011, the 9th European conference on Numerical Mathematics and Advanced Applications, Leicester, September 2011

引用

2016年

作者： Andrea Cangiani Ruslan L Davidchack Emmanuil H Georgoulis Alexander N Gorban Jeremy Levesley Michael v Tretyakov

ISBN: (纸本)9783662511299

The European conferences on Numerical Mathematics and Advanced Applications (ENUMATH) are a series of conferences held every two years to provide a forum for discussion of new trends in numerical mathematics and challenging scientific and industrial applications at the highest level of international expertise. ENUMATH 2011 was hosted by the University of Leicester (UK) from the 5th to 9th September 2011. This proceedings volume contains more than 90 papers by speakers of the conference and gives an overview of recent developments in scientific computing, numerical analysis, and practical use of modern numerical techniques and algorithms in various applications. New results on finite element methods, multiscale methods, numerical linear algebra, and finite difference schemes are presented. A range of applications include computational problems from fluid dynamics, materials, image processing, and molecular dynamics.

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WAvELET-BASED TEXTURE-CHARACTERISTIC morphological COMPONENT ANALYSIS FOR COLOUR image ENHANCEMENT

WAVELET-BASED TEXTURE-CHARACTERISTIC MORPHOLOGICAL COMPONENT...

引用

IEEE International conference on image processing

作者： Jianning Chi Mark Eramian University of Saskatchewan Department of Computer Science 176 Thorvaldson Bldg. 110 Science Place Saskatoon SK S7N 5C9 Canada

ISBN: (纸本)9781467399623

This paper proposes a novel colour image enhancement method which uses wavelet-based texture characteristic morphological component analysis (WT-TC-MCA) to enhance the textural differences in the luminance channel of the colour image. The image enhancement method is intended to be the preprocessing method prior to the use of the colour image segmentation. The input colour image is firstly transformed to CIELab colour space to separate the luminance channel from the chromatic channels. Then only the luminance channel is enhanced by the WT-TC-MCA method to enhance the textural differences between different textures. Therefore, the colour image is enhanced with more differentiate textures while preserving the chromatic information. The experimental results show that the proposed method can enhance different colour image segmentation algorithms more than the state-of-the-art colour image enhancement method.

关键词： image color analysis image segmentation image enhancement Wavelet analysis Histograms Adaptive equalizers image edge detection color image luminance channel adaptive equalisers Edge detection image colour analysis image segmentation image enhancement histograms Wavelet Analysis component analysis image enhancement method

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A Realistic Medical image Segmentation of Abnormal HIv in Blood Cells Using morphological Operations

A Realistic Medical Image Segmentation of Abnormal HIV in Bl...

引用

International conference on Inventive Computation Technologies

作者： v. Mageshwari I. Laurence Aroquiaraj T. Dharani Department of Computer Science Periyar University Salem - 636011 Tamil Nadu India

ISBN: (纸本)9781509012862

images are soft copies of real world objects. image can be represented in the area of digital processing, which can be said as another reproduction of an object. Basically Segmentation is one of the processes of partitioning a digital image into multiple regions and extracting meaningful regions for the future image analysis. The prime objective of this research work is to segment the abnormal HIv cells in blood using morphological operations. The boundary region of the HIv cells in blood is detected and segmented using different morphological operations. Finally image Quality Assessment(IQA) has been carried out using various evaluation measures.

关键词： Cell Segmentation morphological Operations PSNR MD NAE NK AD

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Computing the 2-D image Euler Number by an Artificial Neural Network

Computing the 2-D Image Euler Number by an Artificial Neural...

引用

International Joint conference on Neural Networks

作者： Humberto Sossa Angel Carreon Elizabeth Guevara Raul Santiago Instituto Politecnico Nacional-CIC Instituto Tecnologico de Leon

ISBN: (纸本)9781509006212

We describe for the first time how the Euler number of a 2-D binary image can be obtained by means of Artificial Neural Network (ANN). Calculating the Euler image number is treated as a pattern classification problem. To arrive at the specialized ANN architecture, we perform a partial results analysis provided by a known formulation to compute the Euler image number. We use this analysis for designing the desired ANN architecture. Due to its good functioning characteristics, outcomes with the so-called morphological Neural Perceptron with Dendritic processing (MNPDP) are presented. Numerical as well as experimental results with realistic images to demonstrate the operation and applicability of the proposed approach are reported. Initial results concerning the GPU implementation of the proposed ANN to show that the processing time can be effectively reduced are also provided.

关键词： Euler number computation Artificial neural networks morphological neural networks Artificial neural networks Euler Napier's constant realistic images two dimentional images Pattern recognition processing time

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A PARALLEL, O(N) ALGORITHM FOR UNBIASED, THIN WATERSHED

A PARALLEL, O(N) ALGORITHM FOR UNBIASED, THIN WATERSHED

引用

IEEE International conference on image processing

作者： T. Chabardes P. Dokladal M. Faessel M. Bilodeau PSL Research University - MINES ParisTech CMM Center for Mathematical Morphology 35 rue Saint Honore - Fontainebleau France

ISBN: (纸本)9781467399623

The watershed transform is a powerful tool for morphological segmentation. Most common implementations of this method involve a strict hierarchy on gray tones in processing the pixels composing an image. Those dependencies complexify the efficient use of modern computational architectures. This paper aims at answering this problem by introducing a new way of simulating the waterflood that alleviates the sequential nature of hierachical queue propagation. Simultaneous and disorderly growth is made possible using this method. higher speed is reached and bigger data volume can be processed. Experimental results show that the algorithm is accurate and produces a thin, well centered watershed line.

关键词： Transforms image reconstruction Morphology Computer architecture Lakes Floods Coordinate measuring machines

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