Breaking the MintEye image CAPTCHA in 23 lines of Python

This code does not take a swirled image and solve it. It takes a set of images with various swirl levels and finds the one with shortest sum of edge lengths.

The code does not do any un-swirling of the image. It also uses external libraries to convert to grayscale, apply the Sobel filter and the sum of edges.

I other words, it is far from breaking the swirled CAPTCHA in 23 lines of Python. If you had to write the un-swirling, gray-scaling, Sobel filtering and summation code in Python you'd be looking at a much larger pile-o-code.

The demo and the intent is good. I just wish the title didn't say "23 lines of". I don't think the article would have suffered at all if the title was "Breaking the MintEye image CAPTCHA with Python".

Again, the intent and what is being demonstrated are excellent. The title, in my not-so-humble opinion, is hugely misleading.

> If you had to write the un-swirling, gray-scaling, Sobel filtering and summation code in Python you'd be looking at a much larger pile-o-code

I would also like to point out these are also all very simple operations, which would only take a few lines of Python/C/whatever to do. Python just happens to have a pre-written libraries to save reinventing the wheel.

When someone publishes code and says something like "solved in of " there generally is an implied "my language is better than yours" subliminal message that, for some strange reason, is based on line count.

Let's not debate the merit of line count as a measure of how good a language may or may not be. If we are going to go there I'll write the same solution in APL and we'll start counting characters instead. Again, line or character count, in my opinion, is not a measure of the "superiority" of a language.

The 28 line solution is not pure Python. How do we define pure Python. Let's just say that "solved in of Python" to me means that you download and install Python:

http://www.python.org/download/releases/2.7.3/

Install nothing else whatsoever and write code that solves .

OpenCV, which is what the author used for a couple of aspects of this code, is an extensive (and really cool) C++ library that is being accessed from Python. Here's the source:

https://github.com/Itseez/opencv

I'll leave it up to the reader to find the source for the Sobel method.

A much more honest title could have included something like "solving with lines of Python using OpenCV".

As I said before, the intent of the article and what is being demonstrated are good, no, great. I just wish the title was a little more reflective of reality. That's all. No need to get worked-up. This is not that serious of an issue. Just a comment.

Yikes! They are not. That's a lot of code. I've done a ton of image processing work in both hardware (FPGA) and software (various languages). Swirling, gray-scaling, Sobel filtering and summation collectively are far from "a few lines of Python/C/whatever to do"

> Python just happens to have a pre-written libraries to save reinventing the wheel

That's not true. OpenCV is NOT a Python library, it's nearly 100% C++ as far as I can tell:

https://github.com/Itseez/opencv

That was, in many ways, my point. This is not a solution in 23 lines of Python. Go install Python from Python.org --and NOTHING ELSE-- and solve the problem. Let's see how many lines of Python it takes.

There's nothing wrong with the intent of the author in terms of showing how one can break these CAPTCHA's using edge-length evaluation. I never put any thought into this myself so, yes, I learned something of value from his post. I just wish the title was more genuine, that's all.

Let's analyze. One place CAPTCHA has been used a lot is in comment forms. It increases the opportunity cost of posting a comment via automation by introducing a complicated challenge.

Fair enough. But that doesn't solve the underlying problem (abusive comments). You'll still have abuse and spam, it will just come from humans instead of robots. If I'm a blackhat SEO with a budget, I pay people to solve CAPTCHAs all day and spam the internet (that's what happens).

If you design the comment system to fight abuse from the ground up (e.g., markov chain spam filters, user flagging), you don't need to care anymore wether it's a human or a robot behind the POST, because all the spam actually improves your training set. You defeat spammers with their own data.