An Accurate Algorithm for Automatic Stitching in One Dimension (original) (raw)

The paper addresses the issues in accuracy of various image-stitching algorithms used in the industry today on different types of real-time images. Our paper proposes a stitching algorithm for stitching images in one dimension. The most robust image stitching algorithms make use of feature descriptors to achieve invariance to image zoom, rotation and exposure change. The use of invariant feature descriptors in image matching and alignment makes them more accurate and reliable for a variety of images under different realtime conditions. We assess the accuracy of one such industrial tool, [AUTOSTICH], for our dataset and its underlying Scale Invariant Feature Transform (SIFT) descriptors. The tool’s performance is low in certain scenarios. Our proposed automatic stitching process can be broadly divided into 3 stages: Feature Point Extraction, Points Refinement, and Image Transformation & Blending. Our approach builds on the underlying way a casual end-user captures images through came...