ieee paper on image processing




Histopathological image analysis using image processing techniques: An overview
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This paper reviews computer assisted histopathology image analysis for cancer detection and classification. Histopathology refers to the examination of invasive or less invasive biopsy sample by a pathologist under microscope for locating, analyzing and classifying

Image processing techniques for machine vision
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Image Processing Algorithms are the basis for Image Computer Analysis and Machine Vision. Employing a theoretical foundation Image Algebra and powerful development tools Visual C++, Visual Fortran, Visual Basic, and Visual Java high-level and efficient Computer

Aggregate sizing and shape determination using digital image processing
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Aggregate size and shape measurements are increasingly becoming important issues in the mining, comminution, materials handling, and construction industries. Screening or sieving methods, todays standard method of sizing stone materials, are simply too inefficient for

Technical Report: DeVIDE The Delft Visualisation and Image processing Development Environment
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1.5 Architecture 11 1.5.1 TheModuleandModuleAPI . 12 1.5.2 Module Library 12 1.5.3 ModuleManager . . 14 1.5.4

Image processing based forest fire detection
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A novel approach for forest fire detection using image processing technique is proposed. A rule based color model for fire pixel classification is used. The proposed algorithm uses RGB and YCbCr color space. The advantage of using YCbCr color space is that it can separate

Analysis of various quality metrics for medical image processing
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This paper presents the comparative analysis of various quality metrics for medical image processing . Measurement of image quality is important for many image processing applications. Image quality assessment is closely related to image similarity assessment in

Image processing with multiscale stochastic models
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In this thesis, we develop image processing algorithms and applications for a particular class of multiscale stochastic models. First, we provide background on the model class, including a discussion of its relationship to wavelet transforms and the details of a two

Fine structures preserving Markov model for image processing
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We propose a new model based on a Markovian framework for either binary image restoration or segmentation. We rst show that classical regularization with Ising-model means to minimize length of edges, which is not equivalent with to minimize noise. With

Implementation and evaluation of image processing algorithms on reconfigurable architecture using C-based hardware descriptive languages
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With the advent of mobile embedded multimedia devices that are required to perform a range of multimedia tasks, especially image processing tasks, the need to design efficient and high performance image processing systems in a short time-to-market schedule needs

Automated brain tumor detection and identification using image processing and probabilistic neural network techniques
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In this paper, modified image segmentation techniques were applied on MRI scan images in order to detect brain tumors. Also in this paper, a modified Probabilistic Neural Network (PNN) model that is based on learning vector quantization (LVQ) with image and data

Image processing based intelligent traffic controller
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The frequent traffic jams at major junctions call for an efficient traffic management system in place. The resulting wastage of time and increase in pollution levels can be eliminated on a city-wide scale by these systems. The paper proposes to implement an intelligent traffic

Remote area plant disease detection using image processing
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India being an agro-based economy, farmers experince alot of problem in detecting andpreventing diseases in fauna. So there is a necessacity in detecting diseases in fauna which proves to be effective and conviennent for researchers. Relying on pure naked-eye

Nonlinear techniques for color image processing
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The perception of color is of paramount importance to humans since they routinely use color features to sense the environment, recognize objects and convey information. That is why, it is necessary to use color information for computer vision, because in many practical cases

Image processing techniques for detection of leaf disease
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In agriculture research of automatic leaf disease detection is essential research topic as it prove benefits in monitoring large fields of crops, and thus automatically detect symptoms of disease as soon as they appear on plant leaves. The term disease is usually

Mammogram breast cancer image detection using image processing functions
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Mammogram breast cancer images have the ability to assist physicians in detecting disease caused by cells normal growth. Developing algorithms and software to analyze these images also assist physicians in there daily work. This study that shows the outcome of

Radiographic Testing: Part l Image Processing
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Over the past 30 years, a large amount of research has been conducted to developan automatic (or semiautomatic) system for the radiographic detection and classification of discontinuities in continuous welds. There are two major types of research in this field

Implementation of image processing algorithms on FPGA hardware
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Page 1. IMPLEMENTATION OF IMAGE PROCESSING ALGORITHMS ON FPGA HARDWARE By Anthony Edward Nelson Thesis Submitted to the Faculty of the Graduate School of Vanderbilt University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE in

Extraction of shoreline features by neural nets and image processing
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Assmcr: This paper demonstrates the capability of using neural networks as a tool for delineation of shorelines. The neural nets that we use are multi-layer perceptrons, ie, feed- forward nets with one or more layers of nodes between the input and output nodes. The

Genetic programming on GPUs for image processing .
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The evolution of image filters using Genetic Pro-gramming is a relatively unexplored task. This is most likely due to the high computational cost of evaluating the evolved programs. We use the parallel processors available on modern graphics cards to greatly increase the

A MATLAB based face recognition system using image processing and neural networks
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Automatic recognition of people is a challenging problem which has received much attention during recent years due to its many applications in different fields. Face recognition is one of those challenging problems and up to date, there is no technique that provides a robust

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