An improved framework for identifying and recognizing hand drawn sketches

Abstract

Hand-drawn sketching has usually been performed by humans as an outcome of thoughts, interpretation or communication. Due to the advancement of technology, it becomes necessary to promote interaction between computers and humans. This concept has led to the development of numerous automated applications that can be implemented in several real-time scenarios. One among such applications is automated hand-drawn sketch recognition system. newlineApplications in diverse fields such as image processing, game design and creation have been discovered by hand drawing sketch recognition systems. The sketch could portray anything and the computer must be able to recognize the sketch. Though the objective seems to be simple, it is not the case. This is because, the sketch can be drawn in any different shape and structure and the definition of sketch depends on the artist. The automated system analyses and performs intended operations over the sketch to present the results. newlinePerceiving the merits of sketch recognition based applications, this research work presents three hand-drawn sketch based image retrieval systems in three research phases. These systems function by comparing the sketch passed as query and the images in the database, while returning the user with most relevant results. newlineThe initial phase of the research introduces a hand-drawn sketch recovery and recognition method using the Deep Convolutionary Neural Network (DCNN) based Regularised Particle Swarm Optimization (RPSO). newline