Automated logo-based product separation using machine learning

Logo detection of different brands play an important role in advertisement industry and also in sorting of different products .In this paper a logo based product separation is done using deep learning (R-CNN) model. We collect dataset of logos of different brands and trained them using t

Project Title

Automated logo-based product separation using machine learning

Project Area of Specialization

Artificial Intelligence

Project Summary

Logo detection of different brands play an important role in advertisement
industry and also in sorting of different products .In this paper a logo
based product separation is done using deep learning (R-CNN) model. We
collect dataset of logos of different brands and trained them using transfer
learning Approach. This transfer learning approach reduces number of
images required for training and can be train on CPU with less memory
(RAM) is used. Our contribution is to apply Reduce convolution network
(RCNN) model on our custom data set of logos and get accurate result .In
this study the CIFR10 image data set is used which contain 50,000 training
images that used to train RCNN. After logo recognition we separate
the product through conveyer belt with the help of separators. The servo
motors are used with model MG-945 having torque of 180 degree in this
project .All processing is performed on MATLAB 2019a and training is
done on single-CPU with RAM 8GB and core i-5,3rd generation.
iv

Project Objectives

logo detection in images and in videos is considered a key tack for many
applications .There are many fields where we can apply logo detection and
recognition and have output in good way.
• Vehicle logo Detection
• Logo detection for traffic monitoring
Automated Logo-based Product Separation using Machine Learning 9
• Logo Detection for taxation
• Logo Detection for Advertisement
• Copyright infringement detection
• Contextual content placement
• Logo detection for separation of things in industries

Project Implementation Method

first we collect the data and then label and after labelling then we trained it and after traning we implemented on hardware

Benefits of the Project

Our project about logo recognition and product sorter have wide range of
application in industry .Scope of project is wide as the project brings automation
in sorting industry where human beings are deploy for separation
of different products .Our project aim to introduce a deep learning based
model for logo detection and sorting system for industry in a way to reduce
errors in product separation and also manage the products in effective way.
This project can be implemented on any industry where different types of
products, materials are prepared.

Technical Details of Final Deliverable

we use conyer belt and shown the result

Final Deliverable of the Project

Hardware System

Core Industry

Transportation

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com