{'fraction_non_alphanumeric': 0.018145161290322582, 'fraction_numerical': 0.0, 'mean_word_length': 5.365384615384615, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
AUTOMATIC TIE-POINT GENERATION FOR OBLIQUE AERIAL IMAGERY: AN ALGORITHM

Tie points are pixels that describe the geographic position of the same information in two or more images. They are used in a variety of applications such as geometric image transformations, image mosaicking and three-dimensional model generation. Unfortunately, present methods used to select tie-points are computationally inefficient and prone to error. Moreover, the methods are best suited for imagery taken at nadir. This study examines the feasibility and effectiveness of a new tie-point generation algorithm that utilizes inertial navigation system data and the Laplacian of Gaussian spatial filter. Initial results show that the algorithm can provide matches with sub-pixel accuracy in images that exhibit changes in rotation, scale, and translation. The algorithm can also produce matches that exhibit small errors when applied to images that have the distortions mentioned above plus changes in perspective.