Article

Aryadarsh S, Marian Engineering College; Dhanya Mathew ,Marian Engineering College; Neevan R ,IHRD Engineering College

Image completion means, Restoring the lost part of an image by using available information from the remaining parts of the image itself, it is otherwise called as Image inpainting. There are a number of applications for inpainting, they varies from the restoration of damaged paintings and photographs to the removal/replacement of selected objects. In this paper, we present an algorithm that enhances and extends a previously proposed algorithm and it provides faster inpainting. Using our approach, one can use this to inpaint large regions (e.g. to remove an object etc.) as well as it is used to recover small portions (e.g. restore a photograph by removing cracks etc.). The inpainting method is based on the exemplar based approach. The basic idea behind this approach is to find exemplars (i.e. patches) from the image and replace the lost data with it. This technique can be used for the restoration of damaged photographs or damaged film. In contrast with previous approaches, the technique here introduced has an advantage. That is, it does not require the user to specify where the novel information comes from. This is automatically done (and in a fast way), thereby it allows the system to simultaneously fill-in numerous regions which contain completely different structures and surrounding backgrounds. This paper looks forward to improve the algorithm so that the computational complexity is further improved while retaining the quality of inpainting. Here the inpainting algorithm presented here is not meant to be used for inpainting images, but for videos also. We are also investing methods to improve this algorithm to make it more robust so that it can be used with videos in this paper itself.