Image Edge Detection based on FPGA
Objective
 Sobel operator edge detection.
 FPGA:
 Real-time requirement.
 Accurately locate the image edges.
Overview
 Implementing parallel construction of sobel edge detection enhancement algorithm.
 The algorithm is designed with a FPGA chip and it can process 1024×1024×8 Gray Scale Image successfully.
Proposed System
 VHDL code for Sobel edge enhancement algorithm.
 Implementing in the Xilinx Spartan3 FPGA by ISE9.2i.
Intro ....etc

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looking for ppt n report for Edge detection of angiogram images using the classical image processing techniques ...... ....etc

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hi! i would like to have the matlab code for edge detection of blood vessel of angiogram images using classical image processing techniques like filtering first and then applying histogram equalization technique.
i am in my final year of graduation at NIT-Agartala and requires help for my project. ....etc

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INTRODUCTION
Image enhancement and edge detection are well known digital image signal processing applications that may require two-dimensional (2-D) filter-like computational solutions. These applications usually depend on computation intensive code sections, consisting of the repetition of sequences of operations. They are also characterized by the multi-dimensionality of the data involved. An effective technique in improving the computing performance of such applications has been the design and use of Application Specific ....etc

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EDGE Compact and EDGE Classic Packet Data Performance
Abstract
Even though cellular radio services have been extremely successful in providing untethered voice communications, wireless data services have captured only a limited market share so far. One obstacle for wireless data services is their limited peak bit rates. Existing wireless data rates, up to several tens of kb/s, may be over one order of magnitude short of what is required to make popular applications user-friendly. To accomplish these necessities we go for ....etc

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Presented By:-
Akshay P. Dhande


Study and Comparison of Various Image Edge Detection Techniques
ABSTRACT
Edges characterize boundaries and are therefore a problem of fundamental importance in image processing. Image Edge detection significantly reduces the amount of data and filters out useless information, while preserving the important structural properties in an image. Since edge detection is in the forefront of image processing for object detection, it is crucial to have a good understanding of e ....etc

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EDGE Compact and EDGE Classic Packet Data Performance
Abstract
Even though cellular radio services have been extremely successful in providing untethered voice communications, wireless data services have captured only a limited market share so far. One obstacle for wireless data services is their limited peak bit rates. Existing wireless data rates, up to several tens of kb/s, may be over one order of magnitude short o ....etc

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ABSTRACT: The normal direction of the bone contour in computed tomography (CT) images provides important anatomical information and can guide segmentation algorithms. Since various bones in CT images have different sizes, and the intensity values of bone pixels are generally nonuniform and noisy, estimation of the normal direction using a single scale is not reliable. We propose a multiscale approach to estimate the normal direction of bone edges. The reliability of the estimation is calculated from the estimated results and, after re-scaling, ....etc

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Image Processing for Edge Detection

Edge detection is a fundamental tool used in most image processing applications to obtain information from the frames as a precursor step to feature extraction and object segmentation. This process detects outlines of an object and boundaries between objects and the background in the image. An edge-detection filter can also be used to improve the appearance of blurred or anti-aliased image streams. The basic edge-detection operator is a matrix area gradient operation that determines the level of var ....etc

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ABSTRACT: The normal direction of the bone contour in computed tomography (CT) images provides important anatomical information and can guide segmentation algorithms. Since various bones in CT images have different sizes, and the intensity values of bone pixels are generally nonuniform and noisy, estimation of the normal direction using a single scale is not reliable. We propose a multiscale approach to estimate the normal direction of bone edges. The reliability of the estimation is calculated from the estimated results and, after re-scaling, ....etc

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