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Department of Biomedical EngineeringImage stitching is a well-known method to make panoramic image which has a wide field-of-view and high resolution. It has been used in various fields such as digital map, gigapixel imaging, and 360-degree camera. However, commercial stitching tools often fail, require a lot of processing time, and only work on certain images. The problems of existing tools are mainly caused by trying to stitch the wrong image pair. To overcome these problems, it is important to select suitable image pair for stitching in advance. Nevertheless, there are no universal standards to judge the good image pairs. Moreover, the derived stitching algorithms cannot be compatible with each other because they conform to their own available criteria. Here, we present universal stitching parameters and their conditions for selecting good image pairs. The proposed stitching parameters can be easily calculated through analysis of corresponding features and homography, which are basic elements in feature-based image stitching algorithm. In order to specify the conditions of the stitching parameters, we devised a new method to calculate stitching accuracy for qualifying stitching results into 3 classesgood, bad, and fail. With the classed stitching results, the values of the stitching parameters could be checked how they differ in each class. Through experiments with large datasets, the most valid parameter for each class is identified as filtering level which is calculated in corresponding feature analysis. In addition, supplemental experiments were conducted with various datasets to demonstrate the validity of the filtering level. As a result of our study, universal stitching parameters can judge the success of stitching, so that it is possible to prevent stitching errors through parameter verification test in advance. This paper can greatly contribute to guide for creating high performance and high efficiency stitching software by applying the proposed stitching conditions.ope

Stitching IC Images

Image stitching software is used in many areas such as photogrammetry, biomedical imaging, and even amateur digital photography. However, these algorithms require relatively large image overlap, and for this reason they cannot be used to stitch the integrated circuit (IC) images, whose overlap is typically less than 60 pixels for a 4096 by 4096 pixel image. In this paper, we begin by using algorithmic graph theory to study optimal patterns for adding IC images one at a time to a grid. In the remaining sections we study ways of stitching all the images simultaneously using different optimisation approaches: least squares methods, simulated annealing, and nonlinear programming

360-degree Video Stitching for Dual-fisheye Lens Cameras Based On Rigid Moving Least Squares

Dual-fisheye lens cameras are becoming popular for 360-degree video capture, especially for User-generated content (UGC), since they are affordable and portable. Images generated by the dual-fisheye cameras have limited overlap and hence require non-conventional stitching techniques to produce high-quality 360x180-degree panoramas. This paper introduces a novel method to align these images using interpolation grids based on rigid moving least squares. Furthermore, jitter is the critical issue arising when one applies the image-based stitching algorithms to video. It stems from the unconstrained movement of stitching boundary from one frame to another. Therefore, we also propose a new algorithm to maintain the temporal coherence of stitching boundary to provide jitter-free 360-degree videos. Results show that the method proposed in this paper can produce higher quality stitched images and videos than prior work.Comment: Preprint versio

Laryngoscopic Image Stitching for View Enhancement and Documentation - First Experiences

One known problem within laryngoscopy is the spatially limited view onto the hypopharynx and the larynx through the endoscope. To examine the complete larynx and hypopharynx, the laryngoscope can be rotated about its main axis, and hence the physician obtains a complete view. If such examinations are captured using endoscopic video, the examination can be reviewed in detail at a later time. Nevertheless, in order to document the examination with a single representative image, a panorama image can be computed for archiving and enhanced documentation. Twenty patients with various clinical findings were examined with a 70 rigid laryngoscope, and the video sequences were digitally stored. The image sequence for each patient was then post-processed using an image stitching tool based on SIFT features, the RANSAC approach and blending. As a result, endoscopic panorama images of the larynx and pharynx were obtained for each video sequence. The proposed approach of image stitching for laryngoscopic video sequences offers a new tool for enhanced visual examination and documentation of morphologic characteristics of the larynx and the hypopharynx

Image Stitching System Based on ORB Feature-Based Technique and Compensation Blending

Abstract—The construction of a high-resolution panoramic image from a sequence of input overlapping images of the same scene is called image stitching/mosaicing. It is considered as an important, challenging topic in computer vision, multimedia, and computer graphics. The quality of the mosaic image and the time cost are the two primary parameters for measuring the stitching performance. Therefore, the main objective of this paper is to introduce a high-quality image stitching system with least computation time. First, we compare many different features detectors. We test Harris corner detector, SIFT, SURF, FAST, GoodFeaturesToTrack, MSER, and ORB techniques to measure the detection rate of the corrected keypoints and processing time. Second, we manipulate the implementation of different common categories of image blending methods to increase the quality of the stitching process. From experimental results, we conclude that ORB algorithm is the fastest, more accurate, and with higher performance. In addition, Exposure Compensation is the highest stitching quality blending method. Finally, we have generated an image stitching system based on ORB using Exposure Compensation blending method. Keywords—Image stitching; Image mosaicking; Feature-base