Automated image caption generation using deep learning

Abstract

Image captioning means generating relevant texts from images that describe the image. With the growing advancement of deep learning, automatic image caption generation has become an exciting problem among researchers. Image captioning is used in various fields of computer science including computer vision and NLP. It is helpful in many cases such as visual impairment. Though many research works have already been published on this topic using different deep learning models, we can work with various features of the deep learning models to achieve better accuracy. In this paper, we are focusing on combining several deep-learning models to get the desired accuracy. VGG16 model is used which is a CNN architecture to extract essential features from the image. For the generation of relevant captions, LSTM is adopted rather than RNNs as LSTM generates better captions compared to RNNs and it consumes less time. Finally, the model is trained on Flickr 8k datasets.