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About Match 'n' Style

These days, many people use online stores to purchase clothes, bags, sunglasses, other accessories, home descorations, etc. Often these stores have countless number of items on sale, which makes it difficult for the person to find exactly what he/she is looking for. These websites usually categorise their products according to brand, type of item, sale events and prices. Some even use “broad” color categories, however, human beings can perceive around 10 million colors, and indeed, it is impossible and not feasible to make 10 million categories. Hence, online stores can only categorise their products (manually) into a few very “broad” categories. Lets say you just bought a beautiful blue dress, and want to find a perfectly matching purse online; how will you do that? At best, you can look at all the “blue” purses the store has to offer, but, guess what… the human eye can perceive over 50 shades of blue! Your dress has a particular shade of blue, you will have search through probably hundreds of products to find the matching color and then, narrow down your search to the bag you like best.

So, we present, “Match ‘n’ Style” – a web-based application (currently only for demo purposes), which aims to enhance the user experience by narrowing down their search, in a way, that the results shown match the color of the picture of a dress/shirt/wallpaper (for home décor) uploaded by the user. The users can also use their webcam to take a snap of the shirt they are wearing. To further help the user, the webcam detects the user’s shirt (or upper part of the worn/held clothes) in real-time and allows the use to capture it.

The web-cam based shirt detection only works for Google Chrome at the moment. Users using other browsers can easily upload an image of the item, whose matching color they wish to find.


Tips for Users

  • We recommend that the user crops the image, such that, the image doesn’t contain anything other than their item or a part of the item they wish to match.
  • For best results, the background of the item should be white. In case, it is not white, the item should cover the majority of the image.
  • We are currently using a very small dataset of 62 images taken from the Reebonz store. The results will greatly depend on whether or not an appropriate match exists in our dataset.


  • This is a demo project and not a working Online Store.
  • If you wish to know more about “Match ‘n’ Style” or  use our algorithm in your online store or services, you may contact our team.
  • This is the first version of our app, created in less than 30 hours!
  • There is a huge scope for improvement, which we shall try to achieve soon.


Our Team

Prerna Chikersal

Computer Science Undergraduate at Nanyang Technological University

Budhaditya Bhattacharya

Computer Science Undergraduate at Nanyang Technological University

This app was an entry to a Hackathon, conducted by the Computer Engineering Club of NTU and was developed in less than 30 hours! This Hackathon was sponsored by Reebonz.