Hardware Implementation of Image Edge Detection Using Xilinx System Generator

2014 ◽  
Vol 7 (2) ◽  
pp. 188-198
Author(s):  
C. Sujatha ◽  
D. Selvathi
2013 ◽  
Vol 10 (1) ◽  
pp. 1192-1200
Author(s):  
Cms Amrutha Kumari ◽  
Syed Jahangir Badashah

Medical imaging often involves the injection of contrast agents and subsequent analysis of tissue enhancement patterns. X-ray angiograms are projections of 3D reality into 2D representations, there is a fair amount of self occlusion among the vessels, hence one cannot extract the vessels directly using the image intensities or gradients (edge) alone. Vessels extraction from angiogram images is useful for blood vessels measurement and computer visualizations of the coronary artery. This project describes the algorithm for automatic segmentation of coronary arteries in digital X-ray projections here an improved k-means algorithm is proposed. The performance of the proposed algorithm is compared with other techniques. A methodology for implementing real-time DSP applications on a field programmable gate arrays (FPGA) using Xilinx System Generator (XSG) for Mat lab is presented in this paper. It presents the architecture for Edge Detection using Sobel Filter for image processing using Xilinx System Generator. The design was implemented targeting a Spartan3 a DSP 3400 device (XC3SD3400A-4FGG676C) then a vertex 5 (xc5vlx50-1ff676) .the edge detection methods has been verified successfully with no visually perceptual errors in the resulted images.


Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 885
Author(s):  
Vasile Berinde ◽  
Cristina Ţicală

The aim of this paper is to show analytically and empirically how ant-based algorithms for medical image edge detection can be enhanced by using an admissible perturbation of demicontractive operators. We thus complement the results reported in a recent paper by the second author and her collaborators, where they used admissible perturbations of demicontractive mappings as test functions. To illustrate this fact, we first consider some typical properties of demicontractive mappings and of their admissible perturbations and then present some appropriate numerical tests to illustrate the improvement brought by the admissible perturbations of demicontractive mappings when they are taken as test functions in ant-based algorithms for medical image edge detection. The edge detection process reported in our study considers both symmetric (Head CT and Brain CT) and asymmetric (Hand X-ray) medical images. The performance of the algorithm was tested visually with various images and empirically with evaluation of parameters.


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