How to detect when an image is out of focus?

Question

At times our optical inspection system gets out of focus which results in nonsensical measurements. I\'ve been tasked to develop an \'out of focus\' detector which will be

Answer 1

The key is that in-focus image has much more strong gradients and sharp features. So what I suggest is to apply a Gaussian Laplace filter and then look at the distribution of pixel values of the result. The plot below shows the application of this idea to your images, where black refers to the out of focus image, and red to the one in focus. The in-focus one has much more high values (because the image has more sharp gradients).

When you have the histograms, you can distinguish one from another by comparing e.g. 90%th percentiles of the distributions (which is sensitive to tails). For the out of focus image it is 7 and for the in-focus image it is 13.6 (so twice the difference).

Answer 2

A quick and dirty version of the contrast algorithm is to sum the differences between adjacent pixels - higher sum is more contrast.

Answer 3

That's what I do in OpenCV to detect the focus quality:

Mat grad;
int scale = 1;
int delta = 0;
int ddepth = CV_8U;
Mat grad_x, grad_y;
Mat abs_grad_x, abs_grad_y;
/// Gradient X
Sobel(matFromSensor, grad_x, ddepth, 1, 0, 3, scale, delta, BORDER_DEFAULT);
/// Gradient Y
Sobel(matFromSensor, grad_y, ddepth, 0, 1, 3, scale, delta, BORDER_DEFAULT);
convertScaleAbs(grad_x, abs_grad_x);
convertScaleAbs(grad_y, abs_grad_y);
addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 0, grad);
cv::Scalar mu, sigma;
cv::meanStdDev(grad, /* mean */ mu, /*stdev*/ sigma);
focusMeasure = mu.val[0] * mu.val[0];