I am trying to convert an image into a set of arrays that can be useful for digital processing and analytics for commercial purposes. A code has already been created and it works, but is there any way to reduce the time taken for the code to be executed?

I am trying to convert an image into a set of arrays that can be useful for digital processing and analytics for commercial purposes. A code has already been created and it works, but is there any way to reduce the time taken for the code to be executed?

This is a final stage for the commercialisation of a new form of technology that will need to take into account real time analysis of images taken by the technology.

function pixelseperator()clear all

close all Image=imread('flirpolarcamtest3.png');

Image=uint16(Image); [m,n]=size(Image); Imagex=zeros(m/2,n/2); Imagexrows=zeros((m/2),1); col=1; for ni=1:2:n-1 row=1; for mi=1:2:m-1 Imagexrows(row)=Image(mi,ni); row=row+1;

end col=col+1;

Imagex(:,col)=Imagexrows; end Image0=Imagex;

The average time taken for the code to be actuated was apprximately 0.74 seconds, which was expected but a bit too long for the desired time and contained a bit too many intermediates making the code a bit redundant. I am looking for a way to cut down on redundancues and hence reduce the time taken for processing.

Learn to use MATLAB for problem solving, run scripts, write code and do data analysis and visualization, solve equations, do math operations and manipulate matrices, and formulate your own logic and convert complex problems into MATLAB code and solve them using programming skills.

Please see the MATLAB code and equivalent Numpy code below. Question: How can I get the D variable same in Numpy as MATLAB's?

Classification is a very interesting area of machine learning (ML). Learn the basics of MATLAB and understand how to use different machine learning algorithms using MATLAB, with emphasis on the MATLAB toolbox called statistic and machine learning toolbox. Learn the common classification algorithms.