The project consists in develop a tool that make a classification of latex

gloves taking into account the different features that make the difference

between them using a Matlab code in machine learning.

This project has the purpose to have a tool that classify those gloves in

order to know in which market of the world they could be sold and at

what price. So as to achieve this purpose, it is necessary to collect the data

and prepare them to introduce in the code.

The project can be divided in three different parts; the first one is to make

a research of all the theory about latex gloves, achieve the basic

fundamentals with the program Matlab and the theory about image

processing and machine learning. After that, I will collect the 125 data

and the features to take into account are if the gloves have black spots and

if they are yellow or white colour. With all the material, it will possible

to generate a code in Matlab to prepare all the data and finally, train a

model with machine learning.

After training this model, the classifier performed well, achieving 82%

accuracy. However, it is not perfect because the main mistake has been in

the images taken, some of the gloves had wrinkles, so the code detects

them as black spots. That is why, as a future work, the quality of the

images should be improved in order to not have wrinkles and hence

improve the precision for the classifiers.

Moreover, it has been proven that this tool can be implemented in the

company that has provided the gloves. With that, his plan to sell gloves in

Europe could be feasible if the bath of gloves accomplishes the required

Acceptance Quality Limit but it has not been possible to prove because the

gloves have not been randomly selected to carry out this project. Even so

knowing that the code works, it could be applied to corroborate this fact.