A Modified Automatic Image Stitching Model for Textile and Garment Research Area

This paper presents some techniques for constructing panoramic image stitching from sequences of images captured by cameras from different angle in garment and textile research area. The image stitching representation associates a transformation matrix with each input image. In this paper, an improved SIFT(Scale Invariant Feature Transform) algorithm was used to locate the feature points in the scanned images targeting at the problem of automatically stitching of textile images which were scanned in divided pieces. RANSAC (random sample consensus) method is proposed to to estimate image transformation parameters and to find a solution that has the best consensus with the data. Techniques for estimating and rening camera focal lengths are also presented. In order to reduce accumulated registration errors, global alignment (block adjustment) method is proposed for the whole sequence of images, which results in an optimally registered image stitching. A local alignment technique is also developed which warps each image based on the results of pairwise local image registrations to compensate for small amounts of motion parallax introduced by translations of the camera and other unmodeled distortions.

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