IOSR Journal of Computer Engineering (IOSRJCE) ISSN: 2278-0661, ISBN: 2278-8727 Volume 5, Issue 4 (Sep-Oct. 2012), PP 45-49 www.iosrjournals.org www.iosrjournals.org 45 | Page Image in Painting Techniques: A survey Komal s Mahajan 1 , Prof. M. B. Vaidya 2 1,2 (Computer Engineering Department, AVCOE, Ahamadnagar, India) Abstract : Inpainting is the process of reconstructing lost or deteriorated part of images based on the background information. i. e. image Inpainting fills the missing or damaged region in an image utilizing spatial information of its neighbouring region. Inpainting algorithm have numerous applications. It is helpfully used for restoration of old films and object removal in digital photographs. It is also applied to red-eye correction, super resolution, compression etc. The main goal of the Inpainting algorithm is to modify the damaged region in an image in such a way that the inpainted region is undetectable to the ordinary observers who are not familiar with the original image. There have been several approaches proposed for the image inpainting. This proposed work presents a brief survey of different image inpainting techniques and comparative study of these techniques. In this paper we provide a review of different techniques used for image Inpainting. We discuss different inpainting techniques like image PDE based image inpainting, Exemplar based image inpainting, hybrid inpainting, and texture synthesis based image inpainting and semi-automatic and fast digital Inpainting. Keywords: Exemplar, Eye-correction, Hybrid Inpainting, Inpainting, Object Removal, Patch Propagation, Texture Synthesis, I. INTRODUCTION Nowadays, the image Inpainting technology is a hotspot in computer graphics. And it has important value in a heritage preservation, film and television special effects production, removing redundant objects etc. In the fine art museums, this Inpainting concept is used for degraded paintings. Conventionally Inpainting is carried out by professional artist and usually its very time consuming process because it was the manual process. The main goal of this process is to reconstruct damaged parts or missing parts of image. And this process reconstructs image in such a way that the inpainted region cannot be detected by a casual observer. Inpainting technique has found widespread use in many applications such as restoration of old films, object removal in digital photos, red eye correction, super resolution, compression, image coding and transmission. Image Inpainting reconstruct the damaged region or missing parts in an image utilizing spatial information of neighbouring region. Image Inpainting could also be called as modification and manipulation of an image. In image inpainting we would like to create original image but this is completely unfeasible without the prior knowledge about the image. In case of digital images we only have the image we are working on available to us and thus we are filling in a hole that encompasses an entire object. It is impossible to replace that entire object based on the present‟s information. Considering this as the aim of the inpainting algorithm is not only reconstruct what used to be in that hole. But instead to create a visually pleasing continuation of the data around the hole in such a way that it is not detectable by ordinary observer. Diffusion based Inpainting was the first digital Inpainting approach. In this approach missing region is filled by diffusing the image information from the known region into the missing region at the pixel level. Basically these algorithms are based on theory of variational method and Partial Differential equation (PDE). The diffusion- based Inpainting algorithm produces superb results or filling the non-textured or relatively smaller missing region. The drawback of the diffusion process is it introduces some blur, which becomes noticeable when filling larger regions. All the PDE based in painting models are more suitable for completing small, non-textured target region. The second category of Inpainting is exemplar- based Inpainting algorithm. This method of image Inpainting is an efficient approach to reconstructing large target regions. Exemplar-based Inpainting approach iteratively synthesizes the target region by most similar patch in the source region. These algorithms also overcome the drawbacks of PDE based inpainting. Also it removes smooth effect of the diffusion based Inpainting algorithm. Most Inpainting methods work as follows:- In the first step of Inpainting method the user manually selects the portions of the image that will be restored. The image restoration is done automatically, by filling these regions in with new information coming from the surrounding pixels or from the whole image. The algorithms proposed for Inpainting use the information from surrounding portions of image to inpaint the selected region. There are mainly three approaches for inpainting as follows:-