10.35940/ijitee.C8383.0110321
https://zenodo.org/records/5833475
oai:zenodo.org:5833475
Megha J Panicker
Megha J Panicker
Department. of Computer science and Engineering Delhi Technical Campus GGSIPU, Delhi, India
Vikas Upadhayay
Vikas Upadhayay
Department. of Computer science and Engineering Delhi Technical Campus GGSIPU, Delhi, India
Gunjan Sethi
Gunjan Sethi
Department. of Computer science and Engineering Delhi Technical Campus GGSIPU, Delhi, India
Vrinda Mathur
Vrinda Mathur
Department. of Computer science and Engineering Delhi Technical Campus GGSIPU, Delhi, India
Image Caption Generator
Zenodo
2021
Image, Caption, CNN, Xception, RNN, LSTM, Neural Networks
Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)
Blue Eyes Intelligence Engineering and Sciences Publication(BEIESP)
Publisher
2021-01-30
eng
2278-3075
Creative Commons Attribution 4.0 International
In the modern era, image captioning has become one of the most widely required tools. Moreover, there are inbuilt applications that generate and provide a caption for a certain image, all these things are done with the help of deep neural network models. The process of generating a description of an image is called image captioning. It requires recognizing the important objects, their attributes, and the relationships among the objects in an image. It generates syntactically and semantically correct sentences.In this paper, we present a deep learning model to describe images and generate captions using computer vision and machine translation. This paper aims to detect different objects found in an image, recognize the relationships between those objects and generate captions. The dataset used is Flickr8k and the programming language used was Python3, and an ML technique called Transfer Learning will be implemented with the help of the Xception model, to demonstrate the proposed experiment. This paper will also elaborate on the functions and structure of the various Neural networks involved. Generating image captions is an important aspect of Computer Vision and Natural language processing. Image caption generators can find applications in Image segmentation as used by Facebook and Google Photos, and even more so, its use can be extended to video frames. They will easily automate the job of a person who has to interpret images. Not to mention it has immense scope in helping visually impaired people.