IMAGE CHARACTER RECOGNITION USING CONVOLUTIONAL NEURAL NETWORKS

Abstract

Object Recognition is a challenging and exciting task of computer Vision. Object recognition is to describe a collection of related computer vision tasks which involves identifying objects in images. Image classification involves predicting the class of objects in an image. Object localization refers to identifying the location of objects in an image. Image Annotation in Machine Learning is the process of creating bounding boxes around the localized images. Now with the advance of deep learning and neural networks, we can finally tackle these problems without coming up with various heuristics real time. By now, there are many different algorithms and concepts for object detection published. Just a few are lightweight enough to run them on live interface that results in an appropriate frame rate. Object detection networks are for example the You Look Only Once (in short: YOLO) network or the Faster R- CNN network. In this project our aim was to develop a software application that takes an image and produce the Informative links about the objects present in the image. Our aim in this project is to develop a software product that runs the SSD to identify objects in an image and the identified images are searched in Google API to give appropriate informative links of those objects