After talking to Pfizer, we learned that each drug has a unique RGB value. We did some research and found that drug counterfeiting is prevalent and especially affects the poor, the elderly, and developing countries. To solve this problem, we engineered a way to find the RGB value of a drug by taking a picture with your smartphone and comparing this value with a database of verified RGB values.

What it does

Counter prompts its user to choose a type of medicine and take a picture of the medicine they have. Our app will take the RGB value and compare it with the RGB value of the verified medicine and tell the user whether or not their medicine is a counterfeit.

How we built it

We wrote an image processing algorithm in python that finds the average color of the background and analyzes any pixels with RGB values that are not similar to the background. This analysis gives an RGB value for the medicine in the picture taken and compares it with the RGB values of the verified medicine. If the net change in RGB is within 15 RBG units, the medicine is verified. If not, it is labeled as a counterfeit.

Challenges we ran into

Generating the math behind the RGB algorithm.

Accomplishments that we're proud of

Image analysis and data visualization to isolate the medicine.

What we learned

-Image analysis -Flask -Graphic user interface

What's next for Counter

-Adapting the math algorithm to take into account different camera and image-taking conditions.

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