Join Bill Weinman for an in-depth discussion in this video Solution overview, part of Code Clinic: C++.
There are a number of ways to compare images,…some of them very complex and some very simple.…In general, this is a resource-intensive problem.…At best, an image contains a lot of data.…Each pixel contains several colors, usually three,…sometimes four, and value for each color typically…represented by 24 or 32 bits per pixel.…And a typical image from a modern camera, even a cell phone…camera, can have eight or 16 million or more pixels.…First we need to realize that…we're dealing with a lot of data.…
Even so, it shouldn't be that hard to compare…data between images to find an identical subset.…And if that were all there was to it,…this would be a relatively simple problem.…In reality though, it's not that simple.…Most images on the Internet today, especially…photographic images, are compressed and in JPEG format.…JPEG images typically use a lossy form of compression.…That means that two different files may look…identical visually and not be bit-for-bit identical.…This is the same subsection of two visually identical images.…
Bill introduces challenges and provides an overview of his solutions in C++. Challenges include topics such as statistical analysis, searching directories for images, and accessing peripheral devices.
Visit other courses in the series to see how to solve the exact same challenges in languages like C#, Java, PHP, Python, and Ruby.
Skill Level Intermediate
Q: I am unable to access the Lake Pend Oreille data from outside the U.S.
A: A static copy of this data is provided <a href="https://github.com/lyndadotcom/LPO_weatherdata">here</a> for lynda.com members outside of the U.S
Problem One: Exploring Lake Pend Oreille
Solution overview2m 51s
Problem Two: Image Analysis
Problem Three: Eight Queens
Problem Four: Accessing Peripherals
Problem Five: Recursion and Directories
Problem Six: Building the Web
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