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A novel traffic-tracking system using morphological and Blob analysis

A novel traffic-tracking system using morphological and Blob...

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International conference on Computing, Communication and Applications (ICCCA)

作者： Prabhakar Telagarapu M. v. Nageswara Rao Gulivindala Suresh Department of ECE GMR Institute of Technology Rajam Andhra Pradesh India

A vision-based pedestrian and car tracking system which is able to distinguish between car and pedestrian is possible using morphological processing and Blob analysis. videos are sequence of image frames. Here the algorithm is developed to analyse a frame and the same will be applied to all frames in a video. The unwanted objects in video frame can be removed by converting colour frames into a gray scale and by applying thresholding algorithm. Threshold can be set depending on the object to be detected. Gray scale image will be converted to binary during thresholding process. morphological processing will be applied on binary image to remove small unwanted objects that are presented in a frame. A developed blob analysis technique for extracted binary image facilitates pedestrian and car detection. processing blob's information of relative size and location leads to distinguishing between pedestrian and car. The threshold, morphological and blobs process is applied to all frames in a video and finally original video with tagged cars will be displayed.

关键词： videos Algorithm design and analysis vehicles Computer vision visualization Real time systems Monitoring

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Morphology Approach in image processing

Morphology Approach in Image Processing

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International conference on Intelligent Computational Systems(ICICS’2012);International conference on Mechanical,Automotive and Materials Engineering(ICMAME’2012);International conference on Electronics,Biomedical Engineering and its Applications(ICEBEA’2012);International conference on Ecological,Environmental and Biological Sciences(ICEEBS’2012);International conference on Business,Economics,Management and Behavioral Sciences (ICBEMBS’2012);International conference on Applied Mathematics and Pharmaceutical Sciences(ICAMPS’2012)

作者： Satish Pawar v.K.Banga the Department of Electronics & Communication Engineering from Amritsar College of Engineering and Technology

morphological operators transform the original image into another image through the interaction with the other image of certain shape and size which is known as the structure element. Morphology provides a systematic approach to analyze the geometric characteristics of signals or images, and has been applied widely too many applications such as edge detection, objection segmentation, noise suppression and so on. Morphology aims to extend the binary morphological operators to grey-level images. In order to define the basic morphological operations such as fuzzy erosion, dilation, opening and closing, a general method based upon fuzzy implication and inclusion grade operators is introduced. The fuzzy morphological operations extend the ordinary morphological operations by using fuzzy sets where for fuzzy sets, the union operation is replaced by a maximum operation, and the intersection operation is replaced by a minimum operation.

关键词： Binary morphological, Fuzzy sets, Grayscale morphology, image processing, Mathematical morphology.

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SPATIALLY ADAPTIvE PDES FOR ROBUST image SHARPENING

SPATIALLY ADAPTIVE PDES FOR ROBUST IMAGE SHARPENING

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IEEE International conference on image processing

作者： El Hadji S. Diop Jesus Angulo Center of Mathematical Morphology Mathematics and Systems Department Mines Paris-Tech Fontainebleau France

We present here discrete and continuous partial differential equation (PDE) -based methods for image enhancement/sharpening. Using more robust and spatially adaptive PDEs, multiscale morphological operators that account image features are introduced, and then, used to provide a discrete enhancement operator, thanks to the former Kramer and Bruckner filter. A novel PDE associated to the introduced enhancement operator is established in 2D. Both the discrete and PDE-based sharpening filters are illustrated on synthetic, binary and real images.

关键词： Robustness Equations Morphology image analysis image enhancement Mathematical model Pattern recognition

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image DECONvOLUTION vIA SUPERFAST INvERSION OF A CLASS OF TWO-LEvEL TOEPLITZ MATRICES

IMAGE DECONVOLUTION VIA SUPERFAST INVERSION OF A CLASS OF TW...

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IEEE International conference on image processing

作者： Christopher K. Turnes Doru Balcan Justin Romberg Georgia Institute of Technology USA

In this work we present an efficient method to recover images that have been corrupted by a certain class of image filters. For this class of filters, the image degradation process is described by a linear system of equations involving a two-level Toeplitz matrix with triangular structure on either the block or subblock level. This type of structure has algebraic properties that allow us to adapt "superfast" methods for Toeplitz matrix inversion to the two-level case. Our novel two-level superfast algorithm performs the majority of its calculation with the Fast Fourier Transform and allows us to invert an N × N matrix in O(N log N) with reasonable overhead constant. To demonstrate the power of the algorithm we deblur severely corrupted images in short execution times.

关键词： Convolution vectors Modules (abstract algebra) Complexity theory Accuracy Deconvolution Equations

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PATCH-BASED FEATURE MAPS FOR PIXEL-LEvEL image SEGMENTATION

PATCH-BASED FEATURE MAPS FOR PIXEL-LEVEL IMAGE SEGMENTATION

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European Signal processing conference

作者： Shuoying Cao Saadia Iftikhar Anil Anthony Bharath Imperial College London

ISBN: (纸本)9781467310680

In this paper, we describe the use of phase-invariant complex wavelet filters, coupled to a training process involving a small, high-quality training dataset, to build an image segmentation system capable of performing in very low signal-to-noise, and under conditions of strong object-background contrast change. The three main components of our approach are: i) a patch-based feature description of local phase-invariant orientation fields;ii) a priori ground-truth data;iii) a machine learning method, such as Multilayer Perceptron (MLP) or kernel-based Support vector Machine (SvM), to build an accurate classifier that is customised to the segmentation problem. A key feature of the approach is that it may be easily retrained and is, therefore, more adaptable to different imaging modalities. A representation of phase-invariant local image orientation using geometric algebra is first introduced;this is important to the patch-based approach. The quality of our trained systems is then assessed using Receiver Operating Characteristic (ROC) curves in two different biomedical applications: the human retinal vessel-bed in colour fun-dus images from the publicly available DRIvE database, and the rabbit endothelial cell boundaries of thoracic aorta microscopy images.

关键词： Segmentation visual features Geometric algebra Multilayer Perceptron Support vector Machine Microscopy Retinal imaging images image orientation Wavelet filter maps master element Support vector Network

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EFFICIENT FPGA ARCHITECTURE FOR ORIENTED 1-D OPENING AND PATTERN SPECTRUM

EFFICIENT FPGA ARCHITECTURE FOR ORIENTED 1-D OPENING AND PAT...

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IEEE International conference on image processing

作者： Jan Bartovsky Eva Dokladalova Petr Dokladal Mohamed Akil Faculty of Electrical Engineering University of West Bohemia Czech Republic A3SI ESIEE Paris UMR 8049 LIGM University Paris-Est France Center of Mathematical Morphology Mines Paris-Tech France

This paper deals with a dedicated hardware architecture for 1-D morphological opening and pattern spectrum. These operators allow extraction and measurement of 1-D features in images that is a commonly used technique in image analysis and texture classification. The architecture is based on a recently proposed opening algorithm and makes it possible to obtain arbitrary-oriented opening and granulometry at the same time. Respecting a sequential data access, several instances with different orientation can run in parallel on a single input dataflow, increasing thus the performance (experimentally 414 Mpx/s per opening). It opens applicability of traditionally costly operators in embedded, industrial applications.

关键词： Computer architecture Hardware Morphology Materials Feature extraction Signal processing algorithms Field programmable gate arrays

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3D Edge Detection of Medical images Using Mathematical morphological and Cellular Logic Array processing Techniques

3D Edge Detection of Medical Images Using Mathematical Morph...

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IEEE International conference on Systems, Man, and Cybernetics

作者： G. Ramesh Chandra Towheed Sultana G. Sathya E. G. Rajan Department of CSE V.N.R. Vignana Jyothi Institute of Engg. & Tech. Hyderabad Research Scholar Department of ECE Anna University of Technology Department of Computer Science and Engineering New York Institute of Technology Founder President Pentagram Research Centre

ISBN: (纸本)9781467317139

This paper introduces a novel algorithm called cellular logic array processing for extracting volumetric edges from 3D medical images. A sample MRI image of a human skull is used as a test data for analysis purposes. A comparative study of the algorithm introduced in this paper with existing morphological algorithms has been made and results reported here. In addition, a modified morphological filter based 3D edge detecting algorithm has also been introduced in this paper.

关键词： 3D edge detection Cellular logic array processing Mathematical morphology Edge detection Array processing cellular logic Medical imaging Human Remains observational data images paper

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Fusion of morphological images for Airborne Target Detection

Fusion of Morphological Images for Airborne Target Detection

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International conference on Information Fusion

作者： Alexander Wainwright Jason J. Ford School of Engineering Systems Queensland University of Technology

ISBN: (纸本)9780982443859

Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal-to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

关键词： morphological images Airborne Target Detection processing paradigm

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Comparative analysis of microcalcifications detected in mammogram images by edge detection using fractal hurst co-efficient and fudge factor

Comparative analysis of microcalcifications detected in mamm...

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

作者： P. Shanmugavadivu v. Sivakumar Gandhigram Rural Institute Deemed University Gandhigram

ISBN: (纸本)9781467351416

This paper presents a novel approach for edge detection of microcalcifications masses in mammogram images by combining the potential of Fudge factor and Fractal Hurst co-efficient. This Modified Sobel Edge Detector (MSED) technique detects the edges more precisely than the ones obtained by the conventional Sobel method that uses only Fudge factor. The edge detection mechanism presented in this paper has morphological operations as integrated post-processing component, which is viewed as a tool for extracting the image features like edges and regions. In this paper, a comparative analysis of MSED and the conventional sobel method is presented to highlight the merits of combining the fractal-based Hurst co-efficient and Fudge factor-based sobel edge detection, in comparison with the one with Fudge factor alone.

关键词： Edge detection MSED Fudge factor image Segmentation Digital Mammogram Fractal Dimension Hurst Coefficient. Edge detection Microcalcification image segmentation Fractals Digital Mammography morphological operations

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Selective Noise Removal Method in Low Frequency Region for Fiber Bundle-Based Endoscopy

Selective Noise Removal Method in Low Frequency Region for F...

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IEEE International conference on Systems, Man, and Cybernetics

作者： Cheon Yang Lee Jae-Ho Han Department of Brain and Cognitive Engineering Korea University

ISBN: (纸本)9781467317139

This paper introduces the restoration method of degraded images distorted by inherent structure of fiber bundle. The criterion considered for the restoration is based on morphological processing and notch filter, removing the particular frequency, with auto peak detection. The proposed algorithm achieved effective removal of pixelated artifact such as regular honeycomb pattern by finding particular peaks in Fourier domain. As a series of procedure, we have found optimized parameter for decoupling the noise. Experimental results of contrast-to-noise ratio (CNR) demonstrate numerical enhancement from 3.9dB to 16.7dB. Our proposed method can also be expected to apply other periodic pattern noise.

关键词： Component Endoscopic imaging Fiber optic imaging image processing Optical coherence tomography Honeycomb Pattern fiber-optic bundle modal noise morphological processing restoration Fiber Endoscopes Endoscopy low frequencies pixel peak detection Trap Filter carrier to noise ratios

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