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POHough Transform: improving algorithm efficiency over OpenCL
 

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  1. POHough Transform: improving algorithm efficiency over OpenCL
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    <p>I am trying to detect a circle in binary image using hough transform. </p> <p>When I use Opencv's built-in function for the circular hough transform, it is OK and I can find the circle.</p> <p>Now I try to write my own 'kernel' code for doing hough transform but is very very slow: </p> <pre><code> kernel void hough_circle(read_only image2d_t imageIn, global int* in,const int w_hough,__global int * circle) { sampler_t sampler=CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP_TO_EDGE | CLK_FILTER_NEAREST; int gid0 = get_global_id(0); int gid1 = get_global_id(1); uint4 pixel; int x0=0,y0=0,r; int maxval=0; pixel=read_imageui(imageIn,sampler,(int2)(gid0,gid1)); if(pixel.x==255) { for(int r=20;r&lt;150;r+=2) { // int r=100; for(int theta=0; theta&lt;360;theta+=2) { x0=(int) round(gid0-r*cos( (float) radians( (float) theta) )); y0=(int) round(gid1-r*sin( (float) radians( (float) theta) )); if((x0&gt;0) &amp;&amp; (x0&lt;get_global_size(0)) &amp;&amp; (y0&gt;0)&amp;&amp;(y0&lt;get_global_size(1))) atom_inc(&amp;in[w_hough*y0+x0]); } if(maxval&lt;in[w_hough*y0+x0]) { maxval=in[w_hough*y0+x0]; circle[0]=gid0; circle[1]=gid1; circle[2]=r; } } } } </code></pre> <p>There are source codes for the hough opencl library with opencv, but its hard to me for extract a specific function that helps me.</p> <p>Can anyone offer a better source code example, or help me understand why this is so inefficient? the code main.cpp and kernel.cl compress in rar file <a href="http://www.files.com/set/527152684017e" rel="nofollow">http://www.files.com/set/527152684017e</a> use opencv lib for read and display image ></p>
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