Sketch Based Image Retrieval using Transfer Learning

Sketch based image recognition is an approach where the system recognizes an image from the database based on the query sketch received from the user through an interface. In our implementation, we use transfer learning approach to learn the features of the sketch. Transfer learning is a technique used to reuse a model, which is pretrained, for a new problem thereby enhancing the model accuracy and reducing training time. Sketchy Database is used for training which contains 75,471 sketches of 125 categories. A pretrained VGG19 network is used to find the similarity between the sketch and image database using a cosine similarity function. Based on the result of the similarity function, SBIR recognizes a set of similar images corresponding to the sketch. Since the uses of touch devices are increasing rapidly even in a relatively small area, we focus on our final solution being scalable as well as distributed.