Image Processing Best Practices — C++ Part 3

Soubhi Hadri
6 min readDec 14, 2020

Since you are here, I suppose that you have gone through Part1 and Part2 of this series and, hopefully, found them beneficial. As I promised in part 2 of this series, here is a new article which will help you prepare for your next Computer Vision/Image Processing coding interview.


This article is a continuation of the first & second. Please go back and check the previous articles out if you have not already, since this article heavily depends on them.

The main two sections of this article are:
1. Implementation for Gaussian blur with support to gray scale and colored images.
2. Find the closest face to the camera.

Gaussian Blur

Gaussian blur filter is one of the smoothing filters. The smoothing effect is the result of blurring the image by convolving the famous Gaussian function.

Smoothing filters are used usually to reduce the noise in the image. The Gaussian blur filter’s size must be positive and odd and the width and height are not required to match.




Soubhi Hadri

Software Engineer at Microsoft. Former Computer Vision Engineer at Shiseido Group 資生堂. Interested in drones, CV, ML and DL.