Tutorial - Implementing Structural Similarity for Images

This course will guide you through creating a fully-functional and smart security camera, using a Raspberry Pi or the webcam on your device. The purpose of the application in this course is to detect movement in the video footage and subsequently execute an action, such as sending out an email or an SMS.

Sections covering both the theory and practical applications are included in this course. The theory videos demonstrate the building blocks so that you can understand how it all works. Topics taught in this course include summation notation, image similarity metrics, and video processing. Image similarity is a set of tools that we can use to compare images, which then helps us determine how similar they are.

A Raspberry Pi is not required to benefit from this course. The program can be run using the webcam in your laptop or desktop computer.

Learning goals:

Summation Notation
Image Similarity Metrics:
- Sum Squared Errors
- Mean Squared Errors
- Structural Similarity
Video processing

[yuchen]

Apparently, your video is not a high-quality one in terms of your writing... But I fully understand everything you want to explain and now I think I got all I want. Thank you!

[lironlavy]

Could you provide a link to the next video?

[arunbhyashaswi]

Hey a great Video but can you please make a segment continuing it. It is quite good and I was searching for its next part but failed to.

[YOU-smqd]

Can you provide us with the python implementation of SSIM (Manual function), THANKS A LOT

[bart]

Rip, I came here for someone to explain the mathematics to me only to find a video that does not explain the mathematics

[hashemaljghami]

hello how i use SSIM to compare two video quality in ubuntu os