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Objectives: This work aims to provide a system to arrange images automatically and produce the High-resolution panoramic images of a 360-degree wide range. Methods: This work consists of many stages which start by arranging the set of unordered input images. The Harris corner detector is used in the process of detecting key-points. Euclidean distance measure is used to compute the distance between points and determine matches. The stage of stitching consists of several steps which are detecting key-points, matching, estimating the shifting matrix between images by using Random Sample Consensus (RANSAC) algorithm, aligning, and blending. Findings: Experiments show that this method is able to arrange different sets of images, where samples taken are between 15–18 images. Depending on the threshold values in the verification process applied to the matched points, which range from (0.4 to 0.6), the number of extracted features and the degree of accuracy can be controlled. Also, the process of blending images based on the taking of a different percentage of the overlapping areas according to the proximity to the contact line gave a distinctive blending result. Application: Production of panoramic images are used in real estate photography, the creation of an attractive experience on viewing all location details, and lots of other uses.

360-Degree Panoramic Image Stitching for Un-ordered Images Based on Harris Corner Detection