Image Filtering

Filtering is perhaps the most fundamental operation of image processing and computer vision. It is a fundamental step when you have to deal with tasks like: noise reduction, contour extraction, text recognition, etc. The main filters can be divided in two big categories: low-pass filters (LPF), which help in removing noise, blurring images, etc., and high-pass filters (HPF) that help in finding edges in images. In this post, we are going to talk about: Gaussian Filter, Median Filter, and Bilater Filter and we will see some code example as well as the results of each filter applied to our lena image.

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Why OpenCV uses BGR?

OpenCV is the most popular library for computer vision and image processing. I started using it for my master (it was a beta version 0.98) thesis and I am stil using it. nitially, I did not understand why the images were loaded as BGR and not RGB. Then after having reading few articles, I came back with an answer. Basically, BGR was the common color format used among camera manufacturers and software providers (e.

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Why Lena (or Lenna)?

Nowadays, who approaches Computer Vision and Image Segmentation for the first time, often has to face with the following image: Have you ever ask to yourself who the girl in the picture is and why it is commonly used in Computer Vision? Lena Forsén, previously Söderberg, born Sjööblom (born 31 March 1951), is a Swedish model who appeared as a Playmate in the November 1972 issue of Playboy magazine, as Lenna Sjööblom.

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