A Stitching Method for Large Document Images

In this paper, we are interested in stitching specific types of images such as schemes, cartographies, documents or drawings that have been acquired using a scanner. Because of the size of these documents, it is not possible to make one acquisition even using large scanners. The result of the acquisition is then an image mosaic that needs to be stitched to obtain the entire image. For that purpose, we propose an adaptation of feature based methods that are not directly usable with the images we want to process. Indeed, points of interest (POIs) extraction on the entire image requires too much memory and matching are not always pertinent because of the particularity of these documents. To demonstrate the good performance of our proposition, we present quantitative and qualitative results obtained using two datasets: a set of images divided synthetically and a set of images that have been acquired manually using a scanner.

[1]  David G. Lowe,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.

[2]  Richard Szeliski,et al.  Multi-image matching using multi-scale oriented patches , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[3]  Aseem Agarwala Efficient gradient-domain compositing using quadtrees , 2007, SIGGRAPH 2007.

[4]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[5]  Patrick Pérez,et al.  Poisson image editing , 2003, ACM Trans. Graph..

[6]  David Salesin,et al.  Interactive digital photomontage , 2004, SIGGRAPH 2004.

[7]  Yingen Xiong,et al.  Fast panorama stitching for high-quality panoramic images on mobile phones , 2010, IEEE Transactions on Consumer Electronics.

[8]  Bobby Bodenheimer,et al.  Synthesis and evaluation of linear motion transitions , 2008, TOGS.

[9]  P. Anandan,et al.  About Direct Methods , 1999, Workshop on Vision Algorithms.

[10]  Jiří Matas,et al.  Computer Vision - ECCV 2004 , 2004, Lecture Notes in Computer Science.

[11]  Richard Szeliski,et al.  Vision Algorithms: Theory and Practice , 2002, Lecture Notes in Computer Science.

[12]  Jeremy R. Cooperstock,et al.  Toward Dynamic Image Mosaic Generation With Robustness to Parallax , 2012, IEEE Transactions on Image Processing.

[13]  Richard Szeliski,et al.  Eliminating ghosting and exposure artifacts in image mosaics , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[14]  Shmuel Peleg,et al.  Seamless Image Stitching in the Gradient Domain , 2004, ECCV.

[15]  Yingen Xiong,et al.  Mask-based image blending and its applications on mobile devices , 2009, International Symposium on Multispectral Image Processing and Pattern Recognition.

[16]  Hideo Saito,et al.  Augmenting text document by on-line learning of local arrangement of keypoints , 2009, 2009 8th IEEE International Symposium on Mixed and Augmented Reality.

[17]  Michael Kazhdan,et al.  Streaming multigrid for gradient-domain operations on large images , 2008, SIGGRAPH 2008.

[18]  Luc Van Gool,et al.  Speeded-Up Robust Features (SURF) , 2008, Comput. Vis. Image Underst..

[19]  Dani Lischinski,et al.  Coordinates for instant image cloning , 2009, SIGGRAPH 2009.

[20]  Alexei A. Efros,et al.  Image quilting for texture synthesis and transfer , 2001, SIGGRAPH.

[21]  Chi-Keung Tang,et al.  Image Stitching Using Structure Deformation , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Andrew Zisserman,et al.  Feature Based Methods for Structure and Motion Estimation , 1999, Workshop on Vision Algorithms.

[23]  Mohammad H. Mahoor,et al.  Fast image blending using watersheds and graph cuts , 2009, Image Vis. Comput..

[24]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[25]  Matthew A. Brown,et al.  Automatic Panoramic Image Stitching using Invariant Features , 2007, International Journal of Computer Vision.

[26]  Yalin Wang,et al.  Document zone content classification and its performance evaluation , 2006, Pattern Recognit..

[27]  Jean-Philippe Domenger,et al.  Hierarchical clustering model for pixel-based classification of document images , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).