Posts tagged ‘Blur Detection’

Image Blur Detection via Hough Transform — IV

In my previous three articles (1,2,3) I discussed how to use Canny edge detection and Hough transform to identify blur images. Here I will show some results from the algorithm discussed before. Continue reading ‘Image Blur Detection via Hough Transform — IV’ »

Image Blur Detection via Hough Transform — III

I will continue where I left off in my previous post. After performing Hough transform, and extracted the longest sections of lines for each corresponding Hough line detected, we will need to calculate the gradients of the image pixels luminance around the line sections. Continue reading ‘Image Blur Detection via Hough Transform — III’ »

Image Blur Detection via Hough Transform — II

In my previous post, I briefly discussed the rationale behind automated blur detection in digital imagery and did an overview of an algorithm that could be used to detect blur images. Here I will show some implementation details along with some C++ code snippets. Continue reading ‘Image Blur Detection via Hough Transform — II’ »

Image Blur Detection via Hough Transform — I

It is often necessary to identify and classify images based on their clarities. For instance, it is desirable for an automated process to locate blurred images within a large digitized image library and then automatically sharpen the blurred images via inverse filtering or blind deconvolution. In the following series of articles, I will discuss a practical method in detecting blur images using Hough Transform. Continue reading ‘Image Blur Detection via Hough Transform — I’ »