High Level Modeling and Hardware Implementation of Image Processing Algorithms Using XSG

2020 ◽  
pp. 1033-1045
Author(s):  
Kamel Messaoudi ◽  
Hakim Doghmane ◽  
Hocine Bourouba ◽  
E. B. Bourennane ◽  
S. Toumi
Keyword(s):  
Image Processing ◽  
Hardware Implementation ◽  
High Level Modeling ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
High Level

Hardware Implementation of Image Processing Algorithms on FPGA

2020 ◽  
Author(s):  
Aditi Metkar ◽  
Mansi Maroo ◽  
Abhisha Sawant ◽  
Vanshika Singh ◽  
Sagar Mhatre
Keyword(s):  
Image Processing ◽  
Hardware Implementation ◽  
Image Processing Algorithms ◽  
Processing Algorithms

scholarly journals Image Processing Techniques Based Crowd Size Estimation

2020 ◽  
Vol 12 (3) ◽  
pp. 407-414
Author(s):  
Mohanad Abdulhamid ◽  
◽  
Lwanga Wanjira ◽  
Keyword(s):  
Image Processing ◽  
Theoretical Foundation ◽  
Visual Basic ◽  
Size Estimation ◽  
Image Processing Techniques ◽  
Development Tools ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
High Level ◽  
Processing Techniques

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 vision techniques have been developed. This paper analyzes different image processing algorithms by classifying them in logical groups. In addition, specific methods are presented illustrating the application of such techniques to the real world images. In most cases more than one method is used. This allows a basis for comparison of different methods as advantageous features as well as negative characteristics of each technique is delineated. The main objective of this paper is to use image processing techniques to estimate the size of a crowd from a still photograph. The simulation results show that the different images have different efficiencies.

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