Image Stitching

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performed to generate one panoramic image from a series
Don Bosco Institue of Technology, Mumbai University.
Image stitching or photo stitching is the process of combining of smaller, overlapping images. multiple photographic images with overlapping fields of view
E-mail: meetmirza@yahoo.co.in,anitafernandes05@gmail.com,lobosharon@gmail.com, of invariant
Recently there has been great progress in the use to produce a segmented panorama or high-resolutionpriyanka2908@gmail.com. image. features [3, 4, 5] for object recognition and matching.These
Most approaches to image stitching require nearly exact overlaps features can be found more repeatably and matched more between images and identical exposures to produce seamless reliably than traditional methods such as cross-correlation results. using Harris corners. Harris corners are not invariant to scaling of the image, and cross-correlation of image patches
This project’s goal is to create a script that will stitch two images is not invariant to rotation. However invariant features are together to create one larger image. Image stitching has wide photo applications and has become a required toolset for many designed to be invariant to these transformations. In this work photographers. These stitched images, become panoramic views we use Lowe’s [6] Scale Invariant Feature Transform (SIFT which increase the visual aesthetics of a scene, and are widely features), which are geometrically invariant under similarity sought out for posters, postcards, and other printed materials. transforms and invariant under affine changes in intensity.

Various applications such as mosaicing and object insertion require stitching of image parts. The stitching quality is measured visually by the similarity of the stitched image to each of the input images, and by the visibility of the seam between the stitched images.Image stitching can be helpful for satellite imagery, bio- medical usage and many more.



References: Conference on Computer Vision and Pattern Recognition, pages 774–781, 2000. Machine Vision Conference, pages 253–262, Cardiff, 2002.

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