IMAGE CAPTIONING

2. 142 GOVERNMENT POLYTECHNIC COLLEGE
KELAMANGALAM
REVIEW-01
DEPARTMENT OF COMPUTER
ENGINEERING
IMAGE CAPTIONING USING DEEP LEARNING
FOR MULTILANGUAGE

3. PROJECT MEMBERS
SAHANA .S
AMUDHA .G
DHIVYA .B
MONISHA.Y
SOWMIYA .V
VEDHA SHREE .M
- 23501538
- 23501506
- 23501515
- 23501526
- 23501545
- 23501555
PROJECT GUIDE;
B.SANTHIMEENA. M.E.,HOD..

4. ABSTRACT
 This project's major goal is to Produce a version that makes it
possible to foresee the caption or text that will appear next to
the image.
The creation of captions for pictures is a difficult and
responsible task.
 This image captioning is a complex and challenging tasks.
 The main aim of this project is to develop a model such that it
can predict the closest text or caption to that particular image.

5. INTRODUCTION
The term "photo captioning" refers to the explanation of the image's content.
Picture captions are a brand-new trend that is currently generating a lot of
curiosity.
The main objective of this photo capture is to generate a natural language
description for the entry photo that is sent to the version.
In this analysis, we provide a model that depicts characterization as a
linguistic technique using herbs.
Also, the neural network's functionalities are taken from extraordinary
architectures like CNN and LSTM.

6. EXISTING SYSTEM
In the beginning it is impractical to computer to
characterize an image.
There are still some problems in existing systems.
Disadvantages:
Improving the Quality of Captions.
Not Generating creative captions.
 Handling unseen objects.
 Dealing with multiple objects and relationships are

7. PROPOSED SYSTEM
Image Caption Generator Model (CNN-RNN model)
= CNN + LSTM
A pre-trained model called Xception is used for
this.
CNN – To extract features from the image.
LSTM – To generate a description from the
extracted information of the image.

8. MODULES
 Data pre-processing
 VGG16-Xception
 CNN LSTM
Advantages:
 Efficiency.
 Generating creative captions.

9. SYSTEM REQUIREMENT SPECIFICATION
Processor : Intel or Pentium
Speed : 2.4GHZ
Hard Disk : 1 TB HDD, 256GB SSD
Input : Keyboard, Mouse
Ram : 8GB
HARDWARE REQUIREMENTS

10. SOFTWARE REQUIREMENTS
Operating System - Windows10 or Higher
Dataset - Flickr 8k
Software - Jupyter Notebook