i am working in project right now that one part of it, is related with blur detection and i have seen your article about detecting blur in images by using hough transform

http://www.kerrywong.com/2009/07/03/image-blur-detection-via-hough-transform-iv/

i think that your implementation is quite interesting and i would like to try it. My question are if it possible to have an archive of the code and if you will be able to give me a feedback to some questions that i have at the moments. Since right now i am trying to implement your thoughts by using the OpenCV library.

Thanks in advance. Looking forward to hearing from you.

/*
* File: lineutils.h
* Author: kwong
*
* Created on June 5, 2009, 8:47 PM
*/

#ifndef _LINEUTILS_H
#define _LINEUTILS_H

#include

using namespace std;

namespace KDW {
class LineUtils {
public:

LineUtils();
LineUtils(const LineUtils& orig);
virtual ~LineUtils();

void GetLineIntervalPoints(float p, float theta, float x0, float y0, int numOfPoints, IppiPoint points[]);
void GetPerpendicularLineParameters(float p0, float theta0, float x, float y, float &p, float &theta);
void GetLongestConnectedLinePoints(IppiPoint points[], int len, int threshold, IppiPoint lpoints[], int &maxLen);
bool GetMinMaxIndicies(float pixels[], int len, int &minIndex, int &maxIndex);
float CalculateGradient(IppiPoint points[], float pixels[], int len, int minIndex, int maxIndex);
float GetAverage(float gradients[], int count);
private:
};
}
#endif /* _LINEUTILS_H */

Thany you..

You also showed some situations in which this approach fails, are there any other methods that might get around these shortcomings that you are aware of?

Thanks for sharing.

I just updated the article above to include the LineUtil class which contains the gradient calculation. Hope it helps.

I have my Hough-paramaterised lines but I’m still unclear about how you calculate the gradient in the 10-pixel area around the line segment (in the window which is given by d.)

Could you elaborate on how you implemented the gradient calculation element of the system?

Many thanks for your help.

I am currently a student at the university of La Rochelle, France, in an image processing & mathematics master.
Our teachers asked us to build several image default detector: noise(salt&pepper, ccd), block artifact, color dominance, motion-blur and out-of-focus blur.

I am working since yesterday on your articles for blur detection via Hough Transform.

Working on Matlab, i succesfully reproduce almost everything, except for the final part of the algorythm: the calcul of the gradient on the line.
I didn’t understand what you are doing:
- in which image is this line? In the Hough transform? In the orignal image?
- Similarly, what is the use of the perpendicular line whom you speak of for the gradient calculation?

My principal problem lies with the definition of the gradient D of an image :
In classics way, D=[Ix,Iy] with Ix and Iy being a vector field (Ix(x,y)=I(x,y)-I(x-1,y), the same for Iy). Here i do not know what is it.

If you’re willing to enlight me, i would be thankful.

Antonin.