Image Caption Generation using Deep Neural Networks
J Sudhakar, Viswesh V Iyer, T. Sree Sharmila
Abstract
In recent years, computer vision has made significant progress, primarily in the field of image classification and object detection and recognition. Describing the image content automatically using natural languages is challenging and has a tremendous potential impact. Here, the idea is to extract features from an image, generate captions, and convert the generated captions to speech. This work systematically analyses deep neural networks based image caption generation. With an image as an input, the model can output an English sentence that describes the content in the image by CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), and sentence generation. The generated caption is converted to audio using Google's Text to Speech (gTTS). These models are built on the Flickr 8k dataset consisting of 8000+ images. Usually, human beings tend to describe a scene using natural languages which are compact and concise. However, machine vision systems describe the scene/image by taking an image that is a two-dimensional array.